Triple
T2238931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goldie (Sin City) |
E49347
|
entity |
| Predicate | filmReleaseYearOfFirstAppearance |
P13249
|
FINISHED |
| Object | 2005 |
—
|
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: 2005 | Statement: [Goldie (Sin City), filmReleaseYearOfFirstAppearance, 2005]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmReleaseYearOfFirstAppearance Context triple: [Goldie (Sin City), filmReleaseYearOfFirstAppearance, 2005]
-
A.
yearOfFilmAppearance
Indicates the specific year in which a film appearance by an entity took place.
-
B.
filmReleaseYear
chosen
Indicates the calendar year in which a film was first officially released to the public.
-
C.
seriesDebut
Indicates the first appearance or initial release of a series in which the subject entity is introduced.
-
D.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
-
E.
productionStartYear
Indicates the year in which the production of an item, work, or entity first began.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0bb3fac81908b1e8518951dd160 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.