Triple
T4791771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kangra district |
E106616
|
entity |
| Predicate | hasNotableTown |
P14082
|
FINISHED |
| Object | Palampur |
E470664
|
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: Palampur | Statement: [Kangra district, hasNotableTown, Palampur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palampur Context triple: [Kangra district, hasNotableTown, Palampur]
-
A.
Palampur
chosen
Palampur is a scenic hill town in the Indian state of Himachal Pradesh, known for its tea gardens and views of the Dhauladhar mountain range.
-
B.
Vikrampur
Vikrampur was a historic urban and political center in the Bengal region, renowned as an important seat of power and culture in medieval South Asia.
-
C.
Ganga Gram
Ganga Gram is a rural development initiative focused on transforming villages along the Ganges into model, environmentally sustainable communities.
-
D.
Benipatti
Benipatti is a town in the Madhubani district of the Indian state of Bihar, known for its rural setting and proximity to the region’s famed Mithila culture.
-
E.
Mahipalpur
Mahipalpur is an urban village and commercial area in Delhi, India, located near Indira Gandhi International Airport and known for its hotels, transport hubs, and proximity to major highways.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65ddff388190b55071ed5cae7688 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4d96f7e88190be4ba5c7ceb07608 |
completed | March 21, 2026, 7:49 a.m. |
Created at: March 20, 2026, 1:22 p.m.