Triple
T14067951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karur |
E338524
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Namakkal |
E476038
|
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: Namakkal | Statement: [Karur, hasNearbyCity, Namakkal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Namakkal Context triple: [Karur, hasNearbyCity, Namakkal]
-
A.
Namakkal
chosen
Namakkal is a town in the Indian state of Tamil Nadu known for its historic rock fort, temples, and role as a regional commercial and transport hub.
-
B.
Nannilam
Nannilam is a small town in the Tiruvarur district of Tamil Nadu, India, known for its traditional Tamil culture and rural setting.
-
C.
Vandiyur
Vandiyur is a locality in Madurai, Tamil Nadu, known for its historic temple tank and religious significance.
-
D.
Keelakarai
Keelakarai is a coastal town in Tamil Nadu, India, known for its historic mosques, maritime trading heritage, and culturally rich Muslim community.
-
E.
Palamoor
Palamoor is the historical name of Mahbubnagar, a town and district headquarters in the Indian state of Telangana.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568b81f08190a571004261c0e8e4 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb66aeff8819088239226bbe25fd5 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:21 p.m.