Triple
T8449446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Hit |
E199763
|
entity |
| Predicate | hasCinematographer |
P1953
|
FINISHED |
| Object | Mike Molloy |
E786338
|
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: Mike Molloy | Statement: [The Hit, hasCinematographer, Mike Molloy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mike Molloy Context triple: [The Hit, hasCinematographer, Mike Molloy]
-
A.
Mike Molloy
chosen
Mike Molloy is a cinematographer best known for his work on the British crime film "The Hit."
-
B.
Michael Maloney
Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
-
C.
Mike O’Shea
Mike O’Shea is a Canadian football coach and former linebacker best known for leading the Winnipeg Blue Bombers to multiple Grey Cup championships in the CFL.
-
D.
Greg Mollica
Greg Mollica is an illustrator and designer known for creating book cover art, including the cover of Ta-Nehisi Coates’s novel "The Water Dancer."
-
E.
Christopher Murney
Christopher Murney is an American character actor and voice actor known for his work in film, television, and animation, including a prominent role on the series "Remember WENN."
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09b22da4c81909aacc9c4a6af379c |
completed | April 4, 2026, 5:01 a.m. |
Created at: March 30, 2026, 6:09 p.m.