Triple
T5234114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Ireland |
E118180
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dan Ireland |
E118180
|
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: Dan Ireland | Statement: [Dan Ireland, name, Dan Ireland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Ireland Context triple: [Dan Ireland, name, Dan Ireland]
-
A.
Dan Ireland
chosen
Dan Ireland was a Canadian-American film director and producer best known as the co-founder and former director of the Seattle International Film Festival.
-
B.
Anthony Ireland
Anthony Ireland was a British actor known for his work in mid-20th-century film and theatre.
-
C.
Dan Kavanagh
Dan Kavanagh is the crime-fiction pseudonym used by British novelist Julian Barnes for a series of detective novels.
-
D.
Dan O'Brien
Dan O'Brien is a former American decathlete and Olympic gold medalist widely regarded as one of the greatest decathletes in history.
-
E.
Brian Kavanagh
Brian Kavanagh is a film editor best known for his work on notable Australian and international films, including the drama "The Devil's Playground."
- 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_69bd4467db0881909b3b0982df32cc8f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b04c03481908d901788ce2c4128 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef818f31c8190a26950dcd9d6a895 |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:49 p.m.