Triple
T102055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1912 World Series |
E2059
|
entity |
| Predicate | numberOfGamesScheduled |
P6413
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [1912 World Series, numberOfGamesScheduled, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGamesScheduled Context triple: [1912 World Series, numberOfGamesScheduled, 7]
-
A.
gamesPlayed
Indicates the number or set of games that an entity has participated in or completed.
-
B.
minimumFootballGamesPerSeason
Indicates the minimum number of football games that must be played in a single season.
-
C.
playoffAppearances
Indicates the number of times an entity (such as a team or player) has qualified for and participated in postseason playoff competition.
-
D.
hasPrimeTimeGames
Indicates that an entity (such as a team, league, or event) is associated with games scheduled during prime-time viewing hours.
-
E.
numberOfSports
Indicates the quantity of distinct sports associated with or involved in a given 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2563921f8819087f720b1c803579f |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.