Triple
T14441925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Tyne Daly |
E358101
|
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: [Ellen Tyne Daly, parent, James Daly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: James Daly Context triple: [Ellen Tyne 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.
Jon Daly
Jon Daly is an American comedian and actor known for his work in film and television, including roles in projects like the comedy film "Masterminds."
-
D.
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."
-
E.
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.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de915d28ec81909e72124e9dd67bfb |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd648d8904819084d720a0fd2ddb4b |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:18 a.m.