Triple
T19608371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palampur |
E470664
|
entity |
| Predicate | hasNearbyPlace |
P3449
|
FINISHED |
| Object | Baijnath |
—
|
NE NERFINISHED |
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: Baijnath | Statement: [Palampur, hasNearbyPlace, Baijnath]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baijnath Context triple: [Palampur, hasNearbyPlace, Baijnath]
-
A.
Baijnath
chosen
Baijnath is a historic town in Himachal Pradesh, India, renowned for its ancient Shiva temple and scenic Himalayan surroundings.
-
B.
Kinnaur
Kinnaur is a mountainous district in the Indian state of Himachal Pradesh, known for its dramatic Himalayan landscapes, apple orchards, and rich blend of Hindu and Buddhist culture.
-
C.
Ambarnath
Ambarnath is a suburban city in the Thane district of Maharashtra, India, known for its historic Shiva temple and its role as a residential and industrial hub near Mumbai.
-
D.
Nalagarh
Nalagarh is a historic town and former princely state in Himachal Pradesh, India, known for its hilltop fort and scenic surroundings.
-
E.
Kheragarh
Kheragarh is a town in the culturally significant Braj region of northern India, known for its historical and religious associations with the broader Mathura–Agra area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640c964fc8190bd1cb60f4b233eaa |
completed | April 20, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:43 p.m.