Triple
T8550774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rajinikanth |
E202437
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Baashha |
E202787
|
NE 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: Baashha | Statement: [Rajinikanth, notableWork, Baashha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baashha Context triple: [Rajinikanth, notableWork, Baashha]
-
A.
Baashha
chosen
Baashha is a hugely popular 1995 Tamil action film starring Rajinikanth, celebrated for its iconic dialogues, mass appeal, and enduring cult status in Indian cinema.
-
B.
Baaka
Baaka is the traditional Aboriginal name for the Darling River, one of the major inland rivers of southeastern Australia.
-
C.
Baabda
Baabda is a town in Lebanon that serves as the administrative center of the Mount Lebanon Governorate and hosts the Lebanese presidential palace.
-
D.
Datooga
Datooga is a Southern Nilotic language spoken primarily by the Datooga people of north-central Tanzania.
-
E.
Bisha
Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe75589d8819096177ddbd3dafcb6 |
completed | March 31, 2026, 3:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce892efdf8819093c966bd8f6c8065 |
completed | April 2, 2026, 3:20 p.m. |
Created at: March 30, 2026, 6:19 p.m.