Triple

T20568965
Position Surface form Disambiguated ID Type / Status
Subject Avanti E505038 entity
Predicate neighboringRegion P17964 FINISHED
Object Matsya 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: Matsya | Statement: [Avanti, neighboringRegion, Matsya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matsya
Context triple: [Avanti, neighboringRegion, Matsya]
  • A. Matsya chosen
    Matsya was an ancient Indo-Aryan kingdom of northwestern India, often associated with the region around modern Rajasthan and mentioned in early Vedic and epic literature.
  • B. Matsya
    Matsya is the fish incarnation of the Hindu god Vishnu, known for saving the sacred scriptures and the first man from a great deluge.
  • C. Matsya avatar
    The Matsya avatar is the fish incarnation of the Hindu god Vishnu, known for saving the first man and the sacred scriptures from a great deluge.
  • D. Garsaura
    Garsaura was an ancient settlement in central Anatolia, known as the historical predecessor of the modern Turkish city of Aksaray.
  • E. Ikan
    Ikan is an alternative name for the Ukaan language, a lesser-known Niger-Congo language spoken in parts of Nigeria.
  • 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_69e0b4b721588190993ac7b0a9be2736 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a7a4b90c81909854dac72f671eec completed April 20, 2026, 10:24 p.m.
Created at: April 16, 2026, 11:39 a.m.