Triple
T37533676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neetu Kapoor |
E933132
|
entity |
| Predicate | workedAsChildActorUnderName |
P188211
|
FINISHED |
| Object | Baby Sonia |
—
|
NE NERFINISHED |
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: Baby Sonia | Statement: [Neetu Kapoor, workedAsChildActorUnderName, Baby Sonia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedAsChildActorUnderName Context triple: [Neetu Kapoor, workedAsChildActorUnderName, Baby Sonia]
-
A.
playedByChildActor
Indicates that a role or character is portrayed by an actor who is a child at the time of performance.
-
B.
startedCareerAsChildActor
Indicates that a person began their professional career in acting during childhood.
-
C.
playedEarlyRoleIn
Indicates that one entity contributed significantly to the initial or formative stages of another entity’s development, success, or emergence.
-
D.
creditedRoleOf
Indicates that a particular role or position is formally acknowledged as being held or performed by a specific entity in a credit or attribution context.
-
E.
filmDebutAsChildArtist
Indicates that a person made their first appearance in a film while working in the capacity of a child artist.
- F. None of above. chosen
Provenance (4 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_69f76ec999288190ae26ec7b6aea7046 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba5eec0448190a5e6f0c43fdcd0e3 |
completed | May 6, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69fba34edd548190bfa980e6e16e0a88 |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba5ee00fc81909be7b947a3f95034 |
completed | May 6, 2026, 8:34 p.m. |
Created at: May 3, 2026, 4:17 p.m.