Triple
T11892515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Daly |
E282950
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | James Daly |
E355869
|
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: James Daly | Statement: [Tim Daly, parent, James Daly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Daly Context triple: [Tim Daly, parent, James Daly]
-
A.
James Daly
chosen
James Daly was an American actor known for his work in television and film during the mid-20th century, including roles on series like "Medical Center."
-
B.
James Daly
James Daly is a British Conservative Party politician who serves as the Member of Parliament for the Bury North constituency.
-
C.
Andrew Daly
Andrew Daly is an American actor and comedian known for his work in television, film, and voice acting, including roles on shows like "Review" and "Eastbound & Down."
-
D.
Daniel Dillon
Daniel Dillon is a central character in Thomas Hardy’s novel "The Mayor of Casterbridge," known for his complex moral struggles and tragic personal downfall.
-
E.
Jack Doolan
Jack Doolan is a British actor best known for his role in the coming-of-age comedy-drama film "Cemetery Junction" and various appearances in UK television series.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f6389ba08190b07fac8e90da0f5b |
completed | May 2, 2026, 1:03 p.m. |
Created at: April 8, 2026, 9:44 p.m.