Triple
T14025232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | INS Kadamba |
E337438
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Karwar city |
E102301
|
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: Karwar city | Statement: [INS Kadamba, near, Karwar city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karwar city Context triple: [INS Kadamba, near, Karwar city]
-
A.
Karwar
chosen
Karwar is a coastal city in the Indian state of Karnataka, known for its beaches, port, and role as a key urban center in the Konkan region.
-
B.
Margao
Margao is a major commercial and cultural city in South Goa, India, known for its historic Portuguese influence and role as a gateway to nearby beaches.
-
C.
Tarapur
Tarapur is a town in the Anand district of Gujarat, India, known as a local commercial and agricultural center.
-
D.
Rajkot
Rajkot is a major city in the Indian state of Gujarat, known as an important commercial and cultural center of the Saurashtra region.
-
E.
Sewri
Sewri is a neighborhood in Mumbai, India, known for its railway station on the city’s suburban network and its location along the eastern waterfront.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa6ca7481908976ce748a1957b1 |
completed | April 14, 2026, 12:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcd097814081909835aeed46aa4a59 |
completed | May 7, 2026, 5:49 p.m. |
Created at: April 9, 2026, 10:20 p.m.