Triple
T22973873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 12 Strong |
E571259
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Jeffrey Ford |
—
|
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: Jeffrey Ford | Statement: [12 Strong, editedBy, Jeffrey Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Ford Context triple: [12 Strong, editedBy, Jeffrey Ford]
-
A.
Jeffrey Ford
chosen
Jeffrey Ford is a film editor known for his work on major blockbuster movies, including several entries in the Marvel Cinematic Universe.
-
B.
Jeffrey Ford
Jeffrey Ford is an American fantasy and science fiction author known for his imaginative short stories and novels that blend the surreal with the literary.
-
C.
Laird Barron
Laird Barron is an American author known for his dark, cosmic horror and weird fiction that blends noir sensibilities with unsettling supernatural elements.
-
D.
John Kessel
John Kessel is an American science fiction author and academic known for his award-winning short stories and novels that often blend satire, literary experimentation, and genre tropes.
-
E.
Tim Lebbon
Tim Lebbon is a British horror and dark fantasy author known for his original novels and film tie-in works, including the story that inspired the film "The Silence."
- 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182350b448190a34e5fa0167fd964 |
completed | April 29, 2026, 3:59 a.m. |
Created at: April 17, 2026, 3:48 p.m.