Triple
T1548366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibi Mela |
E33029
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object | Sibi |
E33029
|
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: Sibi | Statement: [Sibi Mela, location, Sibi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sibi Context triple: [Sibi Mela, location, Sibi]
-
A.
Sibi
chosen
Sibi is a historic town and district in the Balochistan region of Pakistan, known for its hot climate and traditional annual cattle and horse fair.
-
B.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
C.
Veeragase
Veeragase is a vigorous and ritualistic folk dance-drama of Karnataka, India, traditionally performed during festivals to depict stories of valor from Hindu mythology.
-
D.
Kishkindha
Kishkindha is the mythical monkey kingdom ruled by Sugriva in the Indian epic Ramayana, where Rama forms an alliance with the vanara army to search for Sita.
-
E.
Sehore
Sehore is a town and district headquarters in central India, located near the state capital Bhopal in Madhya Pradesh.
- 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_69a885ee6db8819099502bc5ce8af881 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90856642c81909d88a679eb265b10 |
completed | March 5, 2026, 4:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad719b6c988190a525539d1a29d8d4 |
completed | March 8, 2026, 12:54 p.m. |
Created at: March 4, 2026, 7:26 p.m.