Triple
T628144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Echo Park |
E15863
|
entity |
| Predicate | inFilmAndTV |
P17240
|
FINISHED |
| Object | frequent filming location in Los Angeles |
—
|
LITERAL 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: frequent filming location in Los Angeles | Statement: [Echo Park, inFilmAndTV, frequent filming location in Los Angeles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inFilmAndTV Context triple: [Echo Park, inFilmAndTV, frequent filming location in Los Angeles]
-
A.
televisionFilm
Indicates that the subject is a television film (a movie produced for or originally distributed via television).
-
B.
popularFilmIndustry
Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
-
C.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
-
D.
producedFilm
Indicates that one entity served as the producer (or production company) responsible for making or financing the creation of a particular film.
-
E.
filmSeries
Indicates that a film is part of, or associated with, a larger film series or franchise.
- F. None of above. chosen
Provenance (4 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.