Triple
T25235851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oo Antava Oo Oo Antava |
E632333
|
entity |
| Predicate | associatedWithActress |
P160083
|
FINISHED |
| Object | Samantha Ruth Prabhu |
—
|
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: Samantha Ruth Prabhu | Statement: [Oo Antava Oo Oo Antava, associatedWithActress, Samantha Ruth Prabhu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithActress Context triple: [Oo Antava Oo Oo Antava, associatedWithActress, Samantha Ruth Prabhu]
-
A.
hasAssociatedActress
chosen
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
B.
associatedWithLeadActorOfFilm
Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
-
C.
associatedWithProducerOfFilm
Indicates that one entity has an association or connection with the producer of a particular film.
-
D.
associatedWithDirectors
Indicates a direct relationship or connection between an entity and one or more film or project directors.
-
E.
associatedWithComposerOfFilm
Indicates a relationship where an entity is connected to the composer who created the musical score for a specific film.
- 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_69e75a8ec5f88190b9eba06ae42b413a |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 21, 2026, 1:07 p.m.