Triple
T16163740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big, Blonde and Beautiful |
E392246
|
entity |
| Predicate | theatricalDebutYear |
P60224
|
FINISHED |
| Object | 2002 |
—
|
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: 2002 | Statement: [Big, Blonde and Beautiful, theatricalDebutYear, 2002]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theatricalDebutYear Context triple: [Big, Blonde and Beautiful, theatricalDebutYear, 2002]
-
A.
debutYear
Indicates the year in which an entity first appeared, was introduced, or made its initial public debut.
-
B.
debutAsLeadActressYear
Indicates the year in which an entity first made her debut as a lead actress.
-
C.
filmDebutIn
Indicates the first film in which a person appeared or participated, marking their debut in cinema.
-
D.
broadwayMusicalDebut
Indicates the event or role through which a person first appeared in a Broadway musical production.
-
E.
madeProfessionalDebutIn
chosen
Indicates the time or event in which an individual first performed or appeared in a professional capacity within a given field or organization.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21e616770819093f16c88722b2a7d |
completed | April 17, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:02 a.m.