Triple
T12118271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sikar Municipal Council |
E288622
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Sikar |
E57493
|
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: Sikar | Statement: [Sikar Municipal Council, cityServed, Sikar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sikar Context triple: [Sikar Municipal Council, cityServed, Sikar]
-
A.
Sikar
chosen
Sikar is a prominent city in northern India known for its historic havelis, educational institutions, and role as a commercial hub in the Shekhawati region.
-
B.
Sakesar
Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
-
C.
Sachkhere
Sachkhere is a town in western Georgia known as a local administrative and economic center in the Imereti region.
-
D.
Chamkoria
Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
-
E.
Surkhob
Surkhob is the historical name of a major river in Central Asia that forms part of what is now known as the Vakhsh River in Tajikistan.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915760d208190b68f5e024b3676ba |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f682397c819085a86a98e079660b |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.