Triple

T19969311
Position Surface form Disambiguated ID Type / Status
Subject NH 16 E480026 entity
Predicate passesThroughCity P416 FINISHED
Object Guntur 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: Guntur | Statement: [NH 16, passesThroughCity, Guntur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guntur
Context triple: [NH 16, passesThroughCity, Guntur]
  • A. Guntur chosen
    Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
  • B. Guntur
    Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
  • C. Kakinada
    Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
  • D. Gudivada
    Gudivada is a town in the Indian state of Andhra Pradesh known as a local commercial and educational center in the Krishna River delta region.
  • E. Machilipatnam
    Machilipatnam is a coastal city in the Indian state of Andhra Pradesh, historically known as a significant port and trading center on the Bay of Bengal.
  • 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_69d8e523c19881909f9197037200dde6 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65bc7c2fc81909b89c549a5f99e4c completed April 20, 2026, 5 p.m.
Created at: April 10, 2026, 1:54 p.m.