Triple

T7017630
Position Surface form Disambiguated ID Type / Status
Subject National Highway 37 E162734 entity
Predicate connects P390 FINISHED
Object Tinsukia E226989 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: Tinsukia | Statement: [National Highway 37, connects, Tinsukia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tinsukia
Context triple: [National Highway 37, connects, Tinsukia]
  • A. Tinsukia chosen
    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.
  • B. Tezpur
    Tezpur is a historic city in northeastern India known for its cultural heritage, archaeological sites, and scenic location on the banks of the Brahmaputra River.
  • C. Dibrugarh
    Dibrugarh is a prominent city in northeastern India known as a major commercial and industrial hub of Assam, especially for its tea industry and oil and natural gas sectors.
  • D. 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.
  • E. Jorhat
    Jorhat is a prominent city in northeastern India known as a cultural and educational hub and a key center of the tea industry in Assam.
  • 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_69c6885a127c8190867b059bdccf13ff completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1e79c108190a507335e9dbf2716 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eebe7d008190990482c7d6b512f5 completed March 28, 2026, 3:07 p.m.
Created at: March 27, 2026, 2:34 p.m.