Triple
T20975733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiruvarur Thyagaraja Temple |
E516619
|
entity |
| Predicate | sacredTankName |
P46222
|
FINISHED |
| Object | Kamalalayam |
—
|
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: Kamalalayam | Statement: [Tiruvarur Thyagaraja Temple, sacredTankName, Kamalalayam]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kamalalayam Context triple: [Tiruvarur Thyagaraja Temple, sacredTankName, Kamalalayam]
-
A.
Kamalaalayam
chosen
Kamalaalayam is the sacred temple tank of the Tiruvarur Thyagaraja Temple, renowned for its lotus-filled waters and religious significance in Tamil Nadu.
-
B.
Urapakkam
Urapakkam is a rapidly developing suburban residential area on the outskirts of Chennai in Tamil Nadu, India.
-
C.
Rayamangalam
Rayamangalam is a village in the Aluva taluk of Ernakulam district in the Indian state of Kerala.
-
D.
Vedalam
Vedalam is a 2015 Tamil-language action film starring Ajith Kumar, known for its mass appeal, high-octane fight sequences, and emotional brother-sister storyline.
-
E.
Nedumkandam
Nedumkandam is a high-range town in Kerala, India, known for its cool climate, cardamom plantations, and location along the Munnar–Thekkady route.
- 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_69e0b4fee5ac8190875fa9ceba1a5e5e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fba3df2081908c1db5f8610ba43d |
completed | April 21, 2026, 4:23 a.m. |
Created at: April 16, 2026, 1:46 p.m.