Triple
T16697504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karnal Lok Sabha constituency |
E405752
|
entity |
| Predicate | assemblySegment |
P63908
|
FINISHED |
| Object | Nilokheri |
E415655
|
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: Nilokheri | Statement: [Karnal Lok Sabha constituency, assemblySegment, Nilokheri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nilokheri Context triple: [Karnal Lok Sabha constituency, assemblySegment, Nilokheri]
-
A.
Nilokheri
chosen
Nilokheri is a town in the Karnal district of Haryana, India, known for its agricultural surroundings and local educational institutions.
-
B.
Nakodar
Nakodar is a prominent town in the Indian state of Punjab, known for its historical significance and cultural heritage within the Jalandhar region.
-
C.
Barwala
Barwala is a prominent town in the Hisar district of Haryana, India, known as a local commercial and administrative center for surrounding rural areas.
-
D.
Baddi
Baddi is an industrial town in the Solan district of Himachal Pradesh, India, known for its large concentration of pharmaceutical and manufacturing units.
-
E.
Randhawa
Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3832e93c48190a594c498e9cc901a |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b27dcef481909ccfe4d3d604b1de |
completed | May 10, 2026, 4:29 p.m. |
Created at: April 10, 2026, 5:19 a.m.