Triple
T2118300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1990 World Series |
E43857
|
entity |
| Predicate | umpireCrewChief |
P6421
|
FINISHED |
| Object |
Eric Gregg
Eric Gregg was a prominent Major League Baseball umpire known for his long tenure in the National League and his participation in several high-profile postseason games.
|
E289285
|
NE FINISHED |
How this triple was built (4 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: Eric Gregg | Statement: [1990 World Series, umpireCrewChief, Eric Gregg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Gregg Context triple: [1990 World Series, umpireCrewChief, Eric Gregg]
-
A.
Jeff Nelson
Jeff Nelson is a Major League Baseball umpire who has served in numerous postseason games, including as a crew chief in the World Series.
-
B.
Jeff Groth
Jeff Groth is a film editor best known for his work on the critically acclaimed 2019 psychological thriller "Joker."
-
C.
Keith Fraase
Keith Fraase is a film editor best known for his work on the movie "Chappaquiddick."
-
D.
Stephen Glenn Martin
Stephen Glenn Martin is an American comedian, actor, writer, musician, and producer renowned for his stand-up comedy, film roles, and banjo performances.
-
E.
Michael Graydon
Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Eric Gregg Triple: [1990 World Series, umpireCrewChief, Eric Gregg]
Generated description
Eric Gregg was a prominent Major League Baseball umpire known for his long tenure in the National League and his participation in several high-profile postseason games.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Eric Gregg Target entity description: Eric Gregg was a prominent Major League Baseball umpire known for his long tenure in the National League and his participation in several high-profile postseason games.
-
A.
Jeff Nelson
Jeff Nelson is a Major League Baseball umpire who has served in numerous postseason games, including as a crew chief in the World Series.
-
B.
Jeff Groth
Jeff Groth is a film editor best known for his work on the critically acclaimed 2019 psychological thriller "Joker."
-
C.
Keith Fraase
Keith Fraase is a film editor best known for his work on the movie "Chappaquiddick."
-
D.
Stephen Glenn Martin
Stephen Glenn Martin is an American comedian, actor, writer, musician, and producer renowned for his stand-up comedy, film roles, and banjo performances.
-
E.
Michael Graydon
Michael Graydon is a retired senior Royal Air Force officer who served as a leading commander of British fighter aviation during the late 20th century.
- F. None of above. chosen
Provenance (5 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb3117c081908c5e748a869d1f9f |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afaf266ed881909206c87c69a2ea95 |
completed | March 10, 2026, 5:41 a.m. |
| NEDg | Description generation | batch_69afafa8012481909c0b4d07c8803bf7 |
completed | March 10, 2026, 5:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb02231588190a2c6dbaf22c15b14 |
completed | March 10, 2026, 5:46 a.m. |
Created at: March 4, 2026, 7:44 p.m.