Triple
T2182067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liv Tyler |
E49065
|
entity |
| Predicate | modelingDebut |
P7549
|
FINISHED |
| Object | early 1990s |
—
|
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: early 1990s | Statement: [Liv Tyler, modelingDebut, early 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelingDebut Context triple: [Liv Tyler, modelingDebut, early 1990s]
-
A.
debutedWith
Indicates that an entity made its first public appearance, release, or introduction in association with another specified entity.
-
B.
debutWork
Indicates the work (such as a book, film, album, or performance) that marks an entity’s first public or professional appearance in a given field.
-
C.
debutYear
chosen
Indicates the year in which an entity first appeared, was introduced, or made its initial public debut.
-
D.
filmDebut
Indicates the first film in which an entity (typically a person) appeared or participated, marking their initial entry into film work.
-
E.
hasModelledFor
Indicates that one entity has served as a model for another entity, typically in a professional or representational context such as art, photography, or fashion.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.