Triple

T7741860
Position Surface form Disambiguated ID Type / Status
Subject Upper Assam E175528 entity
Predicate majorCity P316 FINISHED
Object Sivasagar E658991 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: Sivasagar | Statement: [Upper Assam, majorCity, Sivasagar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sivasagar
Context triple: [Upper Assam, majorCity, Sivasagar]
  • A. Sivasagar chosen
    Sivasagar is a historic town in the Indian state of Assam, renowned for its Ahom-era monuments, temples, and large man-made tanks.
  • B. Tinsukia
    Tinsukia is a town in Assam, India, known as a commercial hub of the region and a gateway to nearby wildlife-rich areas such as Dibru-Saikhowa National Park.
  • C. Nagaon
    Nagaon is a major town and administrative center in the Indian state of Assam, known for its agricultural economy and strategic location in the Brahmaputra Valley.
  • D. Sainthia
    Sainthia is a town in the Birbhum district of West Bengal, India, known as a local commercial and cultural center.
  • E. Sipajhar
    Sipajhar is a town and administrative center in the Indian state of Assam, known for its role as a local hub within Darrang district.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c70387807081909546bc7c209955ef completed March 27, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69cde6a2bdd08190897705615109dae0 completed April 2, 2026, 3:46 a.m.
Created at: March 27, 2026, 4:07 p.m.