Triple
T12695245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bharathapuzha |
E303315
|
entity |
| Predicate | mouthLocation |
P417
|
FINISHED |
| Object | Ponnani |
E843164
|
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: Ponnani | Statement: [Bharathapuzha, mouthLocation, Ponnani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ponnani Context triple: [Bharathapuzha, mouthLocation, Ponnani]
-
A.
Ponnani
chosen
Ponnani is a historic coastal town and former trading port in the Malabar region of Kerala, India, known for its cultural and religious significance, especially in Islamic scholarship.
-
B.
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.
-
C.
Alappuzha
Alappuzha is a coastal city in the Indian state of Kerala, famed for its backwaters, houseboat cruises, and annual Nehru Trophy boat race.
-
D.
Cherthala
Cherthala is a coastal town in the Alappuzha district of Kerala, India, known for its backwaters, coir industry, and proximity to Vembanad Lake.
-
E.
Malappuram
Malappuram is a city and district headquarters in the Indian state of Kerala, known for its rich cultural heritage and rapidly growing urban landscape.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ebd17081909f983567e4b36533 |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f684e2292c8190bffb3a8b6e15029c |
completed | May 2, 2026, 11:12 p.m. |
Created at: April 9, 2026, 5:22 p.m.