Triple
T38509929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York–Penn League |
E921874
|
entity |
| Predicate | hasLastPresident |
P3069
|
FINISHED |
| Object | Ben Hayes |
—
|
NE NERFINISHED |
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: Ben Hayes | Statement: [New York–Penn League, hasLastPresident, Ben Hayes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLastPresident Context triple: [New York–Penn League, hasLastPresident, Ben Hayes]
-
A.
lastPresident
chosen
Indicates that one entity is the most recent individual to have held the office of president of the other entity.
-
B.
previousPresident
Indicates that one person held the office of president immediately before another person.
-
C.
hasPresident
Indicates that an entity holds the position or role of president for another entity.
-
D.
lastFederalLeader
Indicates that one entity is the most recent individual to have served as the federal leader of the other entity.
-
E.
formerPresidentOf
Indicates that one entity previously held, but no longer holds, the official position of president of another entity.
- 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_69f76ea3c5448190aa7002fc1ba3f874 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a00233e2170819084bee0c8f74cc1a4 |
completed | May 10, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_6a0022943fd08190b73007f080d5971d |
completed | May 10, 2026, 6:15 a.m. |
Created at: May 3, 2026, 4:32 p.m.