Triple
T2771040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Rambo |
E61455
|
entity |
| Predicate | firstFilmAppearanceYear |
P18082
|
FINISHED |
| Object | 1982 |
—
|
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: 1982 | Statement: [John Rambo, firstFilmAppearanceYear, 1982]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstFilmAppearanceYear Context triple: [John Rambo, firstFilmAppearanceYear, 1982]
-
A.
yearOfFilmAppearance
chosen
Indicates the specific year in which a film appearance by an entity took place.
-
B.
firstAppearanceFor
Indicates that an entity marks the initial occurrence or debut of another entity within a given context or medium.
-
C.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
-
D.
firstAppeared
Indicates the earliest known time or context in which an entity was introduced, observed, or came into existence.
-
E.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfed608819080988e93df7bdf7c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.