Triple
T29301508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naan Autokaaran |
E742970
|
entity |
| Predicate | performedInFilmSetting |
P52439
|
FINISHED |
| Object | Chennai |
—
|
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: Chennai | Statement: [Naan Autokaaran, performedInFilmSetting, Chennai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performedInFilmSetting Context triple: [Naan Autokaaran, performedInFilmSetting, Chennai]
-
A.
livesInFilmSetting
Indicates that an entity resides or exists within the fictional world or setting depicted in a particular film.
-
B.
performedInScene
Indicates that an action or event took place within a specific scene or setting.
-
C.
portrayedInSetting
Indicates that an entity is depicted or represented within a particular setting, environment, or context.
-
D.
performedInSceneType
Indicates that an action or event was carried out within a scene of a specified type or category.
-
E.
filmSetting
chosen
Indicates the place, time, or environment in which the events of a film are set or take place.
- 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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 28, 2026, 1:10 p.m.