Triple
T12683678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue-Tongue Films |
E303010
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Luke Doolan |
E508471
|
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: Luke Doolan | Statement: [Blue-Tongue Films, hasMember, Luke Doolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luke Doolan Context triple: [Blue-Tongue Films, hasMember, Luke Doolan]
-
A.
Luke Doolan
chosen
Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
-
B.
Sean Duggan
Sean Duggan is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the surname Duggan.
-
C.
Andrew Duggan
Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
-
D.
John Duggan
John Duggan is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the Duggan surname.
-
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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961d68358819095bdaab8adf1dcf0 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739688734819092b14bd3edacd4ef |
completed | May 3, 2026, 12:02 p.m. |
Created at: April 9, 2026, 5:21 p.m.