Triple
T7354870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Slugger’s Wife |
E169596
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Chris Nash
Chris Nash is an actor known for his role in the 1985 romantic comedy film "The Slugger’s Wife."
|
E660474
|
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: Chris Nash | Statement: [The Slugger’s Wife, castMember, Chris Nash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Nash Context triple: [The Slugger’s Wife, castMember, Chris Nash]
-
A.
Stephen John Nash
Stephen John Nash is a Canadian former professional basketball player and two-time NBA Most Valuable Player widely regarded as one of the greatest point guards in NBA history.
-
B.
Gavin Millar
Gavin Millar was a Scottish film and television director, critic, and producer known for his work on British dramas and literary adaptations.
-
C.
Christopher Le Brun
Christopher Le Brun is a British painter, sculptor, and printmaker who served as President of the Royal Academy of Arts in London.
-
D.
Greg Mathieson
Greg Mathieson is an American keyboardist, composer, and producer known for his work in jazz, fusion, and pop music, collaborating with numerous prominent artists.
-
E.
Ben Stevens
Ben Stevens is an American lawyer and former Alaska state senator, best known as the son of longtime U.S. Senator Ted Stevens.
- 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: Chris Nash Triple: [The Slugger’s Wife, castMember, Chris Nash]
Generated description
Chris Nash is an actor known for his role in the 1985 romantic comedy film "The Slugger’s Wife."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chris Nash Target entity description: Chris Nash is an actor known for his role in the 1985 romantic comedy film "The Slugger’s Wife."
-
A.
Stephen John Nash
Stephen John Nash is a Canadian former professional basketball player and two-time NBA Most Valuable Player widely regarded as one of the greatest point guards in NBA history.
-
B.
Gavin Millar
Gavin Millar was a Scottish film and television director, critic, and producer known for his work on British dramas and literary adaptations.
-
C.
Christopher Le Brun
Christopher Le Brun is a British painter, sculptor, and printmaker who served as President of the Royal Academy of Arts in London.
-
D.
Greg Mathieson
Greg Mathieson is an American keyboardist, composer, and producer known for his work in jazz, fusion, and pop music, collaborating with numerous prominent artists.
-
E.
Ben Stevens
Ben Stevens is an American lawyer and former Alaska state senator, best known as the son of longtime U.S. Senator Ted Stevens.
- 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_69c68a59f2288190877ca15c19b1e822 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f10e71fc81909307ca39a61142d3 |
completed | March 27, 2026, 9:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802b490cc8190bbbaf7825e293566 |
completed | March 28, 2026, 4:32 p.m. |
| NEDg | Description generation | batch_69c8061e4f248190bd630568f42e7379 |
completed | March 28, 2026, 4:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c806f439848190bcc0aa434e8059d3 |
completed | March 28, 2026, 4:51 p.m. |
Created at: March 27, 2026, 3:05 p.m.