Triple
T17581677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RoboCop 3 |
E428217
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Gary B. Kibbe |
—
|
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: Gary B. Kibbe | Statement: [RoboCop 3, cinematographyBy, Gary B. Kibbe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gary B. Kibbe Context triple: [RoboCop 3, cinematographyBy, Gary B. Kibbe]
-
A.
Gary B. Kibbe
chosen
Gary B. Kibbe was an American cinematographer best known for his frequent collaborations with director John Carpenter on several of his later films.
-
B.
Galen D. Stucky
Galen D. Stucky is an American chemist renowned for his pioneering work in materials chemistry, particularly in the design and synthesis of porous and mesostructured materials.
-
C.
Frank P. Keller
Frank P. Keller is a film editor best known for his Academy Award-winning work on the 1968 action film "Bullitt."
-
D.
Donald R. Seawell
Donald R. Seawell was an American attorney, theatrical producer, and arts patron best known for his influential role in developing Denver’s cultural landscape.
-
E.
Charles J.D. Schlissel
Charles J.D. Schlissel is a film producer best known for his work on major Hollywood thrillers such as "Flightplan."
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463ce8eb081909257be47d150aa04 |
completed | April 19, 2026, 5:10 a.m. |
Created at: April 10, 2026, 5:50 a.m.