Triple
T23648046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who Wants to Be a Millionaire (U.S. syndicated version) |
E584090
|
entity |
| Predicate | questionCountPerGame |
P15109
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Who Wants to Be a Millionaire (U.S. syndicated version), questionCountPerGame, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: questionCountPerGame Context triple: [Who Wants to Be a Millionaire (U.S. syndicated version), questionCountPerGame, 14]
-
A.
numberOfQuestions
chosen
Indicates the total count of questions associated with or contained in a given entity or context.
-
B.
teamCountPerGame
Indicates the number of teams that participate in a single game or match.
-
C.
endsPerGame
Indicates the number of times something (such as a period, segment, or unit of play) concludes within a single game.
-
D.
gamesPlayed
Indicates the number or set of games that an entity has participated in or completed.
-
E.
gamesFrequency
Indicates how often the related entities engage in playing games together or participate in game-related activities.
- 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b287606881909926de5efd882a76 |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:48 p.m.