Triple
T19031846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Gwynn |
E465759
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gwynn |
—
|
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: Gwynn | Statement: [Tony Gwynn, familyName, Gwynn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwynn Context triple: [Tony Gwynn, familyName, Gwynn]
-
A.
Gwynn
chosen
Gwynn is the surname of Hall of Fame Major League Baseball right fielder Tony Gwynn, renowned for his exceptional hitting ability with the San Diego Padres.
-
B.
Garrick Utley
Garrick Utley was an American television journalist and foreign correspondent best known for his work with NBC News.
-
C.
Jake Hoyt
Jake Hoyt is a rookie LAPD narcotics officer whose moral integrity is tested during a tumultuous day under a corrupt veteran detective in the film "Training Day."
-
D.
Dwighty
Dwighty is a fan nickname for Dwight Fairfield, a nervous but resourceful survivor character from the horror game Dead by Daylight.
-
E.
Everett Kent
Everett Kent was an American politician who served as a Democratic member of the U.S. House of Representatives from Pennsylvania in the early 20th century.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d7410dd08190b08a7c0a2b8d67f3 |
completed | April 20, 2026, 7:35 a.m. |
Created at: April 10, 2026, 12:02 p.m.