Triple
T7647126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1986 New York Mets season |
E173152
|
entity |
| Predicate | regularSeasonWinningPercentage |
P77799
|
FINISHED |
| Object | .667 |
—
|
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: .667 | Statement: [1986 New York Mets season, regularSeasonWinningPercentage, .667]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regularSeasonWinningPercentage Context triple: [1986 New York Mets season, regularSeasonWinningPercentage, .667]
-
A.
regularSeasonWins
Indicates the number of games a team wins during the regular season of a competition.
-
B.
allTimeWinningPercentage
Indicates the proportion of contests or games an entity has won over its entire recorded history, typically expressed as a percentage.
-
C.
seasonRecordWins
Indicates the number of games a team has won during a specific season.
-
D.
seasonWins
Indicates the number of games or competitions a team or individual has won during a specific season.
-
E.
seasonRecord
Indicates the overall performance or results an entity achieved over the course of a specific season (e.g., wins, losses, or comparable outcome metrics).
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf3bd388190a8cb0f13322a7c00 |
completed | March 27, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e9ef1c81909c8bff716541ac1f |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f8195e5c8190835e28d44e19f6ef |
completed | March 27, 2026, 9:35 p.m. |
Created at: March 27, 2026, 3:58 p.m.