Triple
T19815094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Namakkal |
E476038
|
entity |
| Predicate | hasTempleDeity |
P83903
|
FINISHED |
| Object | Lord Hanuman |
—
|
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: Lord Hanuman | Statement: [Namakkal, hasTempleDeity, Lord Hanuman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lord Hanuman Context triple: [Namakkal, hasTempleDeity, Lord Hanuman]
-
A.
Hanuman
chosen
Hanuman is a revered Hindu deity known for his immense strength, unwavering devotion to Lord Rama, and central role in the epic Ramayana.
-
B.
Hanuman Pol
Hanuman Pol is one of the main historic entrance gates of Rajasthan’s Kumbhalgarh Fort, serving as a fortified access point and defensive structure.
-
C.
Anjaneya
Anjaneya is another name for the Hindu deity Hanuman, revered as a symbol of strength, devotion, and selfless service.
-
D.
Narasimha
Narasimha is the fierce man-lion incarnation of the Hindu god Vishnu, known for destroying the demon king Hiranyakashipu to protect his devotee Prahlada.
-
E.
Rama
Rama is a river in Bosnia and Herzegovina that flows through mountainous terrain before joining the Neretva River.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654f861248190a633dd8d227d9697 |
completed | April 20, 2026, 4:31 p.m. |
Created at: April 10, 2026, 1:50 p.m.