Triple
T27005716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1985 New York Mets season |
E680234
|
entity |
| Predicate | statLeader |
P5184
|
FINISHED |
| Object | Dwight Gooden – 24 wins |
—
|
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: Dwight Gooden – 24 wins | Statement: [1985 New York Mets season, statLeader, Dwight Gooden – 24 wins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statLeader Context triple: [1985 New York Mets season, statLeader, Dwight Gooden – 24 wins]
-
A.
leagueLeaderIn
Indicates that an entity is the current top-ranked or leading participant within a specified league or competition.
-
B.
leagueLeader
Indicates that the subject entity is currently ranked first or holds the top position within a specified league or competitive grouping.
-
C.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
D.
hitsLeader
Indicates that an entity performs a hitting action on another entity who is in a leader role.
-
E.
hasStatisticalLeaderCategory
chosen
Indicates that an entity is associated with a specific category under which it is recognized as a statistical leader (e.g., in performance metrics or records).
- 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_69eeeb53939c8190bd431f32b060f01f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f621d2c9548190afac336fb182c365 |
completed | May 2, 2026, 4:09 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 7 a.m.