Triple
T11687311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khandwa district |
E277775
|
entity |
| Predicate | hasNotableTown |
P14082
|
FINISHED |
| Object | Harsud |
E271226
|
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: Harsud | Statement: [Khandwa district, hasNotableTown, Harsud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harsud Context triple: [Khandwa district, hasNotableTown, Harsud]
-
A.
Harsud
chosen
Harsud is a historic town in Madhya Pradesh, India, known for being submerged and relocated due to the construction of the Indira Sagar Dam on the Narmada River.
-
B.
Harsil
Harsil is a serene Himalayan village in Uttarakhand, India, known for its apple orchards, scenic river valley, and as a stopover on the route to the Gangotri temple.
-
C.
Dudhrej
Dudhrej is a town in the Surendranagar district of Gujarat, India, known for its residential areas and proximity to the city of Surendranagar.
-
D.
Harnai
Harnai is a town in Pakistan’s Balochistan province known for its coal mining and mountainous terrain.
-
E.
Dhundhari
Dhundhari is an Indo-Aryan language spoken primarily in and around Jaipur and adjoining regions of Rajasthan, India.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4654be881909bd0256cf18e25de |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef14431f3c81908af9167c46f8c2bc |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.