Triple
T516629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttar Pradesh |
E10722
|
entity |
| Predicate | bordersState |
P224
|
FINISHED |
| Object | Himachal Pradesh |
E15088
|
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: Himachal Pradesh | Statement: [Uttar Pradesh, bordersState, Himachal Pradesh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Himachal Pradesh Context triple: [Uttar Pradesh, bordersState, Himachal Pradesh]
-
A.
Himachal Pradesh
chosen
Himachal Pradesh is a mountainous state in northern India known for its Himalayan landscapes, hill stations, and tourism.
-
B.
Uttarakhand
Uttarakhand is a northern Indian state in the Himalayas known for its sacred rivers, pilgrimage sites, and mountainous landscapes.
-
C.
Jammu and Kashmir
Jammu and Kashmir is a northern region of the Indian subcontinent known for its mountainous terrain, strategic location, and long-standing political and territorial disputes.
-
D.
Haryana
Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
-
E.
Meghalaya
Meghalaya is a hilly state in northeastern India known for its heavy rainfall, lush forests, and diverse indigenous cultures.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f184c3a481909bf60bb627b0ea88 |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac82de53808190a105311397acfef6 |
completed | March 7, 2026, 7:56 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.