Triple
T14024911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian Naval Academy |
E337431
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ezhimala, Kerala |
E337431
|
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: Ezhimala, Kerala | Statement: [Indian Naval Academy, locatedIn, Ezhimala, Kerala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ezhimala, Kerala Context triple: [Indian Naval Academy, locatedIn, Ezhimala, Kerala]
-
A.
Ezhimala, Kerala
chosen
Ezhimala, Kerala is a coastal region in northern Kerala that hosts the Indian Naval Academy, one of the world’s largest naval training institutions.
-
B.
Kakkanad
Kakkanad is a rapidly developing suburban region of Kochi in Kerala, India, known as an administrative hub and major IT and industrial center.
-
C.
Mavelikkara
Mavelikkara is a town in the Alappuzha district of Kerala, India, known for its cultural heritage and historical significance.
-
D.
Kayadhu
Kayadhu is a figure in Hindu mythology known as the wife of the demon king Hiranyakashipu and the mother of the devotee Prahlada.
-
E.
Angamaly
Angamaly is a town in the Ernakulam district of Kerala, India, known as a major transportation hub and gateway to the nearby Cochin International Airport.
- 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_69fbc33170ec8190b0ffe41a567a590b |
completed | May 6, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:20 p.m.