Triple
T18534103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narsinh Mehta |
E452916
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Talaja |
—
|
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: Talaja | Statement: [Narsinh Mehta, birthPlace, Talaja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talaja Context triple: [Narsinh Mehta, birthPlace, Talaja]
-
A.
Talaja
chosen
Talaja is a town in the Bhavnagar district of Gujarat, India, known for its historic Jain temples and proximity to the Shatrunjaya hills.
-
B.
Eurajoki
Eurajoki is a municipality in western Finland, known for hosting the Olkiluoto nuclear power plant on the coast of the Gulf of Bothnia.
-
C.
Nietjärvi
Nietjärvi is a lake and surrounding area in eastern Finland known primarily as the site of a significant World War II battle between Finnish and Soviet forces.
-
D.
Jalasjärvi
Jalasjärvi is a former municipality in western Finland, known for its rural landscapes and location along major transport routes.
-
E.
Rautjärvi
Rautjärvi is a municipality in South Karelia, southeastern Finland, known for its rural landscapes, lakes, and proximity to the Russian border.
- 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_69d8d387b5548190aa030dad2cb4947e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53400d548819080b17f30b3ee7174 |
completed | April 19, 2026, 7:58 p.m. |
Created at: April 10, 2026, 11:37 a.m.