Triple

T7801465
Position Surface form Disambiguated ID Type / Status
Subject Krishna district E180442 entity
Predicate hasHeadquarters P62 FINISHED
Object Machilipatnam E698363 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: Machilipatnam | Statement: [Krishna district, hasHeadquarters, Machilipatnam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Machilipatnam
Context triple: [Krishna district, hasHeadquarters, Machilipatnam]
  • A. Machilipatnam chosen
    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.
  • B. Rajahmundry
    Rajahmundry is a historic city in the Indian state of Andhra Pradesh, known as a major cultural and commercial center in the Godavari region.
  • C. Madanapalle
    Madanapalle is a prominent town in the Indian state of Andhra Pradesh, known for its educational institutions and as the place where Rabindranath Tagore translated "Jana Gana Mana" into English.
  • D. Guntur
    Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
  • E. 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.
  • 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_69ca827e50cc8190a92a733577184938 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae988bc2081909870bae1c2e9c238 completed March 30, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cbdec158788190aae5038ea72f2a99 completed March 31, 2026, 2:48 p.m.
Created at: March 30, 2026, 4:33 p.m.