Triple
T654397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted |
E11614
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Michael Barrett |
E104613
|
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: Michael Barrett | Statement: [Ted, cinematographyBy, Michael Barrett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Barrett Context triple: [Ted, cinematographyBy, Michael Barrett]
-
A.
Michael Barrett
chosen
Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
-
B.
Sean Kilpatrick
Sean Kilpatrick is an American professional basketball player known for his scoring ability as a guard in the NBA and overseas leagues.
-
C.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
-
D.
Christian O'Connell
Christian O'Connell is a British radio DJ, comedian, and author best known for hosting popular breakfast shows in the UK and Australia.
-
E.
Michael Callaghan
Michael Callaghan is one of the children of former UK Prime Minister James Callaghan.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4bb5b881908a18b5ec1c94e0cf |
completed | March 1, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaad456481908cf9fb412bdf90f0 |
completed | March 8, 2026, 9:31 p.m. |
Created at: March 1, 2026, 7:36 p.m.