Triple
T21428608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twinkle Khanna |
E528624
|
entity |
| Predicate | yearsActiveAsActress |
P15974
|
FINISHED |
| Object | 1995–2001 |
—
|
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: 1995–2001 | Statement: [Twinkle Khanna, yearsActiveAsActress, 1995–2001]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearsActiveAsActress Context triple: [Twinkle Khanna, yearsActiveAsActress, 1995–2001]
-
A.
activeYearsInFilm
chosen
Indicates the span of years during which an entity was actively involved in film-related work or roles.
-
B.
debutAsLeadActressYear
Indicates the year in which an entity first made her debut as a lead actress.
-
C.
hasFilmCareer
Indicates that an entity has been professionally involved in the film industry as a career.
-
D.
occupationOfActress
Indicates that the specified occupation is the professional role held by a person who is an actress.
-
E.
startedActingCareer
Indicates that an entity began their professional work or involvement in acting at a specific time or event.
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee813db52c8190ac933bc6ec4dbf77 |
completed | April 26, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:49 p.m.