Triple
T23074397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boudica (2003 film) |
E575286
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Rob Lane |
—
|
NE NERFINISHED |
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: Rob Lane | Statement: [Boudica (2003 film), composer, Rob Lane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rob Lane Context triple: [Boudica (2003 film), composer, Rob Lane]
-
A.
Rob Lane
chosen
Rob Lane is a British composer best known for his work on film and television scores, including the soundtrack for "The Damned United."
-
B.
Scott Lane
Scott Lane is a participant featured in the documentary series "Shots in the Dark," which follows photographers working on the overnight crime beat.
-
C.
Mike Lane
Mike Lane is the charismatic male stripper and aspiring entrepreneur portrayed by Channing Tatum in the Magic Mike film series.
-
D.
Mike Lane
Mike Lane is an actor best known for his role in the 1956 boxing drama film "The Harder They Fall."
-
E.
Chris Lehane
Chris Lehane is an American political strategist and communications expert known for advising high-profile Democratic campaigns and figures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245be28d48190ad1348d5a73db37d |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c61bb7c8190a3d9b1fba173cdff |
completed | April 29, 2026, 4:43 a.m. |
Created at: April 17, 2026, 3:56 p.m.