Triple
T13549265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saroo Brierley |
E323597
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Khandwa |
E114390
|
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: Khandwa | Statement: [Saroo Brierley, birthPlace, Khandwa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khandwa Context triple: [Saroo Brierley, birthPlace, Khandwa]
-
A.
Khandwa
chosen
Khandwa is a city in central India known as a regional commercial and cultural center in the state of Madhya Pradesh.
-
B.
Jambusar
Jambusar is a town in the Bharuch district of Gujarat, India, known for its historical significance and regional trade and agriculture.
-
C.
Jhabua
Jhabua is a town and administrative district headquarters in western Madhya Pradesh, India, known for its significant tribal population and culture.
-
D.
Ratlam
Ratlam is a prominent commercial city in western Madhya Pradesh, India, known for its railway junction, textile and chemical industries, and production of gold and silver jewelry.
-
E.
Chandwad
Chandwad is a town in the Nashik district of Maharashtra, India, known for its historical temples and hill forts.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafdcecf481909999a173b32a58cd |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f794281fb48190882f164df1def07e |
completed | May 3, 2026, 6:30 p.m. |
Created at: April 9, 2026, 9:45 p.m.