Triple
T14626789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cliff DeYoung |
E343368
|
entity |
| Predicate | hasWorkedWith |
P9615
|
FINISHED |
| Object | Robin Tunney |
E327180
|
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: Robin Tunney | Statement: [Cliff DeYoung, hasWorkedWith, Robin Tunney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robin Tunney Context triple: [Cliff DeYoung, hasWorkedWith, Robin Tunney]
-
A.
Robin Tunney
chosen
Robin Tunney is an American actress known for her roles in films like "The Craft" and "Empire Records" and the TV series "The Mentalist."
-
B.
Emma Tennant
Emma Tennant was a British novelist known for her experimental, often fantastical fiction and for reimagining classic literary works.
-
C.
Kara Tointon
Kara Tointon is an English actress best known for her roles in television dramas and soap operas such as EastEnders and for winning the BBC competition Strictly Come Dancing.
-
D.
Kit Curran
Kit Curran is a British television sitcom character portrayed by Denis Lawson, known for his scheming, ambitious personality in a local radio station setting.
-
E.
Colleen Anne Fitzpatrick
Colleen Anne Fitzpatrick is an Australian actress known for her work in film, television, and 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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb46a4a9081908472b0a542028a7f |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cd952ec8190ae3013297e81309e |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:26 a.m.