Triple
T37376904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Brooks Was Here" |
E928011
|
entity |
| Predicate | linkedToLocationInFilm |
P60251
|
FINISHED |
| Object | Shawshank State Prison |
—
|
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: Shawshank State Prison | Statement: ["Brooks Was Here", linkedToLocationInFilm, Shawshank State Prison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedToLocationInFilm Context triple: ["Brooks Was Here", linkedToLocationInFilm, Shawshank State Prison]
-
A.
placementInFilm
Indicates the specific position or occurrence of something within the sequence or structure of a film.
-
B.
filmLocationForCharacter
Indicates that a specific location is used as the filming site for scenes involving a particular character.
-
C.
basedInFilm
chosen
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
-
D.
filmLocationFor
Indicates a relationship where a specific place serves as the filming location for a particular film or production.
-
E.
dataLocationOnFilm
Indicates that specific data is stored or recorded at a particular physical position on a piece of film.
- F. None of above.
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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 3, 2026, 4:16 p.m.