Triple
T15442061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HP-14 |
E369928
|
entity |
| Predicate | usedIn |
P98
|
FINISHED |
| Object | Nalagarh |
E1186943
|
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: Nalagarh | Statement: [HP-14, usedIn, Nalagarh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nalagarh Context triple: [HP-14, usedIn, Nalagarh]
-
A.
Nalagarh
chosen
Nalagarh is a historic town and former princely state in Himachal Pradesh, India, known for its hilltop fort and scenic surroundings.
-
B.
Naraingarh
Naraingarh is a town in the northern Indian state of Haryana, known for its agricultural surroundings and role as a local commercial center.
-
C.
Kishangarh
Kishangarh is a town and legislative assembly constituency in Rajasthan, India, known for its marble industry and distinctive miniature paintings.
-
D.
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.
-
E.
Chikhaldara
Chikhaldara is a hill station in Maharashtra, India, known for its cool climate, coffee plantations, and scenic views of the surrounding Satpura ranges.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ef55f5c8190a32b1b6ad1daf454 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbba9fb08190b800af317f0c9abf |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 3:21 a.m.