Triple

T12091958
Position Surface form Disambiguated ID Type / Status
Subject Jawaharlal Nehru Technological University, Kakinada E287965 entity
Predicate city P40 FINISHED
Object Kakinada E56424 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: Kakinada | Statement: [Jawaharlal Nehru Technological University, Kakinada, city, Kakinada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kakinada
Context triple: [Jawaharlal Nehru Technological University, Kakinada, city, Kakinada]
  • A. Kakinada chosen
    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.
  • B. Guntur
    Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
  • C. 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.
  • 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 (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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9151797988190b0d007ea806bcf02 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8b788308190bd9c3b68569bc56a completed May 3, 2026, 2:53 a.m.
Created at: April 8, 2026, 9:48 p.m.