Triple
T1844396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Silver |
E41249
|
entity |
| Predicate | thesisTopic |
P24329
|
FINISHED |
| Object | reinforcement learning |
—
|
LITERAL FINISHED |
How this triple was built (2 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: reinforcement learning | Statement: [David Silver, thesisTopic, reinforcement learning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thesisTopic Context triple: [David Silver, thesisTopic, reinforcement learning]
-
A.
researchTopic
chosen
Indicates that a subject conducts or focuses research on a particular topic or area of study.
-
B.
thesisType
Indicates the specific category or kind of thesis associated with an academic work or degree.
-
C.
coreThesis
Indicates that something expresses, embodies, or constitutes the central argument or main claim within a larger work, discussion, or theory.
-
D.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
E.
undergraduateThesis
Indicates that one entity is an undergraduate student’s thesis work, authored or completed under the supervision or within the academic program of another entity.
- F. None of above.
Provenance (3 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdb0d2c8190a67f584e67979fa3 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.