Triple
T19597552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aluva taluk |
E470385
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Ayyampuzha |
—
|
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: Ayyampuzha | Statement: [Aluva taluk, containsSettlement, Ayyampuzha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ayyampuzha Context triple: [Aluva taluk, containsSettlement, Ayyampuzha]
-
A.
Muvattupuzha
Muvattupuzha is a town in the Indian state of Kerala known as a commercial and transportation hub at the confluence of three rivers.
-
B.
Vythiri
Vythiri is a scenic hill town and popular tourist destination in Kerala, India, known for its lush forests, plantations, and cool climate in the Wayanad district.
-
C.
Mattoor
Mattoor is a locality in the Indian state of Kerala known for housing the historic Thiru Vellaman Thulli Siva Temple.
-
D.
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.
-
E.
Parakkadavu
chosen
Parakkadavu is a village in the Ernakulam district of Kerala, India, known for its rural setting and proximity to the town of Aluva.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407c52c081908704d3a4dd6e853b |
completed | April 20, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:43 p.m.