Triple
T16589046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naseeruddin Shah |
E403033
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mandi |
E481986
|
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: Mandi | Statement: [Naseeruddin Shah, notableWork, Mandi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mandi Context triple: [Naseeruddin Shah, notableWork, Mandi]
-
A.
Mandi
Mandi is a historic town and important commercial and cultural center located along the Beas River in the Indian state of Himachal Pradesh.
-
B.
Mandi
chosen
Mandi is a critically acclaimed 1983 Indian satirical film directed by Shyam Benegal, known for its ensemble cast and sharp social commentary on politics, morality, and the sex trade.
-
C.
Mandi Kani
Mandi Kani is the wife of renowned South African actor, director, and playwright John Kani.
-
D.
Manjhand
Manjhand is a town in Pakistan’s Sindh province, situated within the Jamshoro District along the Indus River region.
-
E.
Machhlishahr
Machhlishahr is a town and administrative subdivision in the Jaunpur district of Uttar Pradesh, India, known for its local markets and regional connectivity.
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3599e79288190b6bcdb6fe4a2d1fa |
completed | April 18, 2026, 10:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007599dcd4819089bbd0569b3d9a12 |
completed | May 10, 2026, 12:10 p.m. |
Created at: April 10, 2026, 5:16 a.m.