Triple
T29376088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soundarya Rajinikanth |
E745000
|
entity |
| Predicate | cinemaRegion |
P167137
|
FINISHED |
| Object | Kollywood |
—
|
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: Kollywood | Statement: [Soundarya Rajinikanth, cinemaRegion, Kollywood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cinemaRegion Context triple: [Soundarya Rajinikanth, cinemaRegion, Kollywood]
-
A.
theatricalRegion
Indicates the geographic area or market where a theatrical performance, production, or release is presented or distributed.
-
B.
hasTheaterSubregion
Indicates that a theater is located within, or is a part of, a specific subregion of a larger geographic or administrative area.
-
C.
primaryFilmingRegions
Indicates the main geographic areas where the filming or production of a work primarily took place.
-
D.
cinemaType
Indicates the specific category or kind of cinema associated with an entity (e.g., multiplex, art house, drive-in).
-
E.
cinemaOf
Indicates a relationship where a cinema is associated with, belongs to, or is located within a particular place, organization, or context.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f669adca6c81909efccc10634f9a63 |
completed | May 2, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f663ff176c8190aaadb475f75daee4 |
completed | May 2, 2026, 8:52 p.m. |
Created at: April 28, 2026, 2:31 p.m.