Triple
T21109166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulzar |
E520129
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Aandhi |
—
|
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: Aandhi | Statement: [Gulzar, notableWork, Aandhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aandhi Context triple: [Gulzar, notableWork, Aandhi]
-
A.
Aandhi
chosen
Aandhi is a 1975 Hindi political drama film, loosely inspired by the life of Indian Prime Minister Indira Gandhi, renowned for Suchitra Sen’s powerful lead performance.
-
B.
Baradal
Baradal is a small uninhabited island in the Tobago Cays of St. Vincent and the Grenadines, known for its protected sea turtle nesting sites and popular snorkeling beaches.
-
C.
Varsha
Varsha is the monsoon season in the Hindu lunisolar calendar, marked by heavy rains and agricultural renewal.
-
D.
Varṣā
Varṣā is the Sanskrit term for the rainy season, particularly associated with the monsoon period in the Indian subcontinent and in traditional Hindu calendrical systems.
-
E.
Grishma
Grishma is the hot summer season in the Hindu lunisolar calendar, typically associated with intense heat and dry weather.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b509a318819092fbbcb21d1fe603 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7210110a48190a6359b6732f6293d |
completed | April 21, 2026, 7:02 a.m. |
Created at: April 16, 2026, 2:54 p.m.