Triple
T17461523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sirmaur district |
E425160
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Nahan |
—
|
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: Nahan | Statement: [Sirmaur district, hasTown, Nahan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nahan Context triple: [Sirmaur district, hasTown, Nahan]
-
A.
Nahan
chosen
Nahan is a small hill town and municipal council in Himachal Pradesh, India, known for its scenic surroundings, pleasant climate, and role as a regional administrative and commercial center.
-
B.
Ahan
Ahan is a lesser-known Niger-Congo language spoken in parts of Nigeria, closely related to and geographically adjacent to Ukaan.
-
C.
Nawalane
Nawalane is a residential neighborhood located within the Lyari area of Karachi, Pakistan.
-
D.
Nasib
Nasib is a given name most notably borne by Nasib Yusifbeyli, an Azerbaijani statesman and political figure of the early 20th century.
-
E.
Nawat
Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a3c4cc8190937808e3272272c0 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.