Triple
T7657943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Observational selection effects and probability |
E173432
|
entity |
| Predicate | mainSubject |
P3
|
FINISHED |
| Object |
Sleeping Beauty problem
The Sleeping Beauty problem is a famous philosophical and probabilistic puzzle about self-locating belief, asking how an agent should update their credences when they are uncertain about both outcomes and their own temporal location.
|
E679749
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sleeping Beauty problem | Statement: [Observational selection effects and probability, mainSubject, Sleeping Beauty problem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sleeping Beauty problem Context triple: [Observational selection effects and probability, mainSubject, Sleeping Beauty problem]
-
A.
Forever Undecided
Forever Undecided is a logic puzzle book by Raymond Smullyan that playfully explores Gödel’s incompleteness theorems through self-referential riddles and dialogues.
-
B.
St. Petersburg paradox
The St. Petersburg paradox is a famous problem in probability theory and economics that highlights how a lottery with an infinite expected payoff can still attract only a finite price from rational gamblers, challenging traditional notions of expected value and decision-making under risk.
-
C.
Happy Ending problem
The Happy Ending problem is a famous combinatorial geometry question that investigates the minimum number of points in general position in the plane needed to guarantee the existence of a convex polygon with a given number of vertices.
-
D.
Ellsberg paradox
The Ellsberg paradox is a famous problem in decision theory and economics that demonstrates how people’s choices often violate expected utility theory due to ambiguity aversion.
-
E.
Sorites paradox
The Sorites paradox is a classic philosophical puzzle about vagueness that questions when the gradual removal or addition of small parts leads to a significant change, such as when a heap of sand stops being a heap.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sleeping Beauty problem Triple: [Observational selection effects and probability, mainSubject, Sleeping Beauty problem]
Generated description
The Sleeping Beauty problem is a famous philosophical and probabilistic puzzle about self-locating belief, asking how an agent should update their credences when they are uncertain about both outcomes and their own temporal location.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sleeping Beauty problem Target entity description: The Sleeping Beauty problem is a famous philosophical and probabilistic puzzle about self-locating belief, asking how an agent should update their credences when they are uncertain about both outcomes and their own temporal location.
-
A.
Forever Undecided
Forever Undecided is a logic puzzle book by Raymond Smullyan that playfully explores Gödel’s incompleteness theorems through self-referential riddles and dialogues.
-
B.
St. Petersburg paradox
The St. Petersburg paradox is a famous problem in probability theory and economics that highlights how a lottery with an infinite expected payoff can still attract only a finite price from rational gamblers, challenging traditional notions of expected value and decision-making under risk.
-
C.
Happy Ending problem
The Happy Ending problem is a famous combinatorial geometry question that investigates the minimum number of points in general position in the plane needed to guarantee the existence of a convex polygon with a given number of vertices.
-
D.
Ellsberg paradox
The Ellsberg paradox is a famous problem in decision theory and economics that demonstrates how people’s choices often violate expected utility theory due to ambiguity aversion.
-
E.
Sorites paradox
The Sorites paradox is a classic philosophical puzzle about vagueness that questions when the gradual removal or addition of small parts leads to a significant change, such as when a heap of sand stops being a heap.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c69955517c819085bc715b96d304d2 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7019161548190855a5b1e9f5d7e99 |
completed | March 27, 2026, 10:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b0d345081909a1d4475fa3876f5 |
completed | March 29, 2026, 3:22 a.m. |
| NEDg | Description generation | batch_69c89d77b7cc81908120da0121c94537 |
completed | March 29, 2026, 3:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89ddd81a88190924d41529e94b06b |
completed | March 29, 2026, 3:34 a.m. |
Created at: March 27, 2026, 3:59 p.m.