Triple
T32794848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester Greenburg |
E838731
|
entity |
| Predicate | hasOnScreenYearOfDebut |
P18082
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Chester Greenburg, hasOnScreenYearOfDebut, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenYearOfDebut Context triple: [Chester Greenburg, hasOnScreenYearOfDebut, 2000]
-
A.
yearInception
Indicates the year in which something (such as an entity, event, or organization) was first established, created, or began.
-
B.
hasOnScreenDebutActor
Indicates that an actor makes their first on-screen appearance in the referenced work or production.
-
C.
yearOfFilmAppearance
chosen
Indicates the specific year in which a film appearance by an entity took place.
-
D.
filmSeriesDebutYear
Indicates the calendar year in which a film series was first released or made its initial debut.
-
E.
workReleaseYearOfAppearance
Indicates the year in which a particular work was first released or made its initial appearance.
- 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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7764ab1fc81909f9348db87bd7692 |
completed | May 3, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f76905d9c88190b1ee810bc9ab644f |
completed | May 3, 2026, 3:25 p.m. |
Created at: May 1, 2026, 1:14 a.m.