Triple
T17206256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Z (film score) |
E417609
|
entity |
| Predicate | hasTypeOfUseInFilm |
P126403
|
FINISHED |
| Object | underscore |
—
|
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: underscore | Statement: [Z (film score), hasTypeOfUseInFilm, underscore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfUseInFilm Context triple: [Z (film score), hasTypeOfUseInFilm, underscore]
-
A.
usedInProductionOfFilm
Indicates that something (such as a resource, tool, or material) was utilized during the making or production process of a film.
-
B.
basedOnInFilm
Indicates that a film is derived from, adapted from, or otherwise uses as its source material another work, event, or concept.
-
C.
usesFilmFormat
Indicates that one entity employs or is recorded in a particular film format associated with the other entity.
-
D.
basedInFilm
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.
-
E.
inheritedByInFilm
Indicates that a character, role, or attribute is passed on or taken over by another character within the narrative of a film.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42dc193488190a2c5a48ce7f631a9 |
completed | April 19, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:38 a.m.