Triple
T509427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yankee Stadium |
E10572
|
entity |
| Predicate | firstRegularSeasonGameDate |
P14544
|
FINISHED |
| Object | 2009-04-16 |
—
|
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: 2009-04-16 | Statement: [Yankee Stadium, firstRegularSeasonGameDate, 2009-04-16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstRegularSeasonGameDate Context triple: [Yankee Stadium, firstRegularSeasonGameDate, 2009-04-16]
-
A.
firstNightGameDate
Indicates the date on which an entity’s first night game took place.
-
B.
lastGameDate
Indicates the date on which the most recent game involving the given entity took place.
-
C.
featuresRegularSeasonGames
Indicates that the subject includes or hosts games that are part of a standard, scheduled regular season competition.
-
D.
hasRegularSeasonGamesAgainst
Indicates that one team or participant plays scheduled, recurring competitive games against another during the regular season.
-
E.
firstGameOpponent
Indicates that one entity is the opponent faced by another entity in its first game or match.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f164a9d48190b525a97b5c06ffe2 |
completed | Feb. 28, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69a2edfe236481909901cc7d4281b33c |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.