Triple
T21032726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shimla district |
E518103
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Narkanda |
—
|
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: Narkanda | Statement: [Shimla district, contains, Narkanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Narkanda Context triple: [Shimla district, contains, Narkanda]
-
A.
Narkanda
chosen
Narkanda is a scenic hill station in Himachal Pradesh, India, known for its apple orchards, skiing slopes, and panoramic Himalayan views.
-
B.
Tanakpur
Tanakpur is a small town in Uttarakhand, India, known as a gateway to the Kumaon region and a key transit point to the neighboring country of Nepal.
-
C.
Karanpur
Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
-
D.
Bilaspuri
Bilaspuri is an Indo-Aryan language spoken primarily in the Bilaspur region of Himachal Pradesh in northern India.
-
E.
Nakodar
Nakodar is a prominent town in the Indian state of Punjab, known for its historical significance and cultural heritage within the Jalandhar region.
- 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_69e0b503275c8190afd9a163f997c709 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc83828c81909c1ec745c0313c9f |
completed | April 21, 2026, 4:26 a.m. |
Created at: April 16, 2026, 1:56 p.m.