Triple
T9740873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashton |
E236180
|
entity |
| Predicate | notableBearer |
P458
|
FINISHED |
| Object | Ashton Eaton |
E79434
|
NE 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: Ashton Eaton | Statement: [Ashton, notableBearer, Ashton Eaton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ashton Eaton Context triple: [Ashton, notableBearer, Ashton Eaton]
-
A.
Ashton Eaton
chosen
Ashton Eaton is an American decathlete and two-time Olympic gold medalist who formerly held the world record in the decathlon.
-
B.
Jeffrey Gaines
Jeffrey Gaines is an American singer-songwriter and guitarist known for his emotive vocal style and acoustic rock performances.
-
C.
Edwin Moses
Edwin Moses is an American track and field legend best known for his dominance in the 400-meter hurdles, including an unprecedented winning streak and multiple Olympic gold medals.
-
D.
Matthew Centrowitz Jr.
Matthew Centrowitz Jr. is an American middle-distance runner best known for winning the gold medal in the 1500 meters at the 2016 Rio Olympics.
-
E.
Aaron Lohr
Aaron Lohr is an American actor and singer known for his roles in films like "The Mighty Ducks" series and "Newsies," as well as for his work in musical theatre.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2af3e48190b83a442cd0e84062 |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afe974608190874e2aba2189de80 |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:22 p.m.