Triple
T19424756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shirvan |
E485952
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Salyan |
—
|
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: Salyan | Statement: [Shirvan, hasCity, Salyan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salyan Context triple: [Shirvan, hasCity, Salyan]
-
A.
Salyan
chosen
Salyan is a town in Azerbaijan known for its location in the Kura River lowlands and its role as a regional administrative and economic center.
-
B.
Andkhoy
Andkhoy is a town in northern Afghanistan known historically as a regional trading center near the Turkmenistan border.
-
C.
Sairang
Sairang is a small town in the Indian state of Mizoram, known for its scenic riverside setting and role as a transport and trading hub near the state capital Aizawl.
-
D.
Parwanoo
Parwanoo is an industrial town in the Solan district of Himachal Pradesh, India, known for its manufacturing units and proximity to the Haryana border.
-
E.
Damauli
Damauli is a town in central Nepal that serves as the administrative headquarters of Tanahun District and a key junction along major transport routes.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63217bd2c81909e216e13aa4c487d |
completed | April 20, 2026, 2:03 p.m. |
Created at: April 10, 2026, 1:37 p.m.