Triple
T35722185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Million Dollar Password |
E1032503
|
entity |
| Predicate | contestantObjective |
P187607
|
FINISHED |
| Object | win up to one million dollars |
—
|
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: win up to one million dollars | Statement: [Million Dollar Password, contestantObjective, win up to one million dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contestantObjective Context triple: [Million Dollar Password, contestantObjective, win up to one million dollars]
-
A.
opponentObjective
Indicates that one entity is the target or goal that an opposing entity aims to counter, defeat, or prevent from succeeding.
-
B.
contestantOn
Indicates that one entity participates as a competitor in a contest, show, or competition associated with another entity.
-
C.
gameObjective
Indicates the primary goal or intended outcome that participants aim to achieve within a game.
-
D.
actorObjective
Indicates that an actor has a specific goal, purpose, or intended outcome in relation to another entity or situation.
-
E.
competitionGoal
Indicates that one entity’s objective or desired outcome is defined in the context of a competition involving another entity.
- F. None of above. chosen
Provenance (4 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_69f76e102b5881909e5d63a30a5cecbe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb6fdab95c81909acff3c6a2359787 |
completed | May 6, 2026, 4:44 p.m. |
Created at: May 3, 2026, 4:05 p.m.