Triple
T5738012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aayega Aanewala |
E126545
|
entity |
| Predicate | filmTitle |
P9968
|
FINISHED |
| Object | Mahal |
E545511
|
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: Mahal | Statement: [Aayega Aanewala, filmTitle, Mahal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahal Context triple: [Aayega Aanewala, filmTitle, Mahal]
-
A.
Mahal
chosen
Mahal is a landmark 1949 Indian Hindi-language psychological horror film, celebrated for pioneering the Bollywood gothic romance genre and launching Madhubala to stardom.
-
B.
Mahal
Mahal is a royal title historically used in the Mughal Empire to denote a queen or high-ranking consort in the imperial harem.
-
C.
Mahala
Mahala is the given first name of Mahalia Jackson, the legendary American gospel singer known as the “Queen of Gospel.”
-
D.
Luisita
Luisita is a Spanish feminine given name, typically used as a diminutive or affectionate form of Luisa.
-
E.
Makili
Makili is a small coastal settlement on Atauro Island in East Timor, known for its traditional fishing community and proximity to rich marine biodiversity.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0255c8c308190821f968ec41c5078 |
completed | March 22, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097f655e881909f6944e9a9d27e6c |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:47 p.m.