Triple

T4514326
Position Surface form Disambiguated ID Type / Status
Subject Rahul Gandhi E102118 entity
Predicate constituencyRepresented P192 FINISHED
Object Wayanad E208519 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: Wayanad | Statement: [Rahul Gandhi, constituencyRepresented, Wayanad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wayanad
Context triple: [Rahul Gandhi, constituencyRepresented, Wayanad]
  • A. Wayanad chosen
    Wayanad is a scenic hill district in Kerala, India, known for its lush forests, wildlife sanctuaries, waterfalls, and spice plantations.
  • B. Malabar District
    Malabar District was a former administrative region in southwestern India under British rule, later incorporated into the state of Kerala.
  • C. Kasargod district
    Kasargod district is a northern Kerala district in India known for its linguistic diversity, coastal landscapes, and cultural blend of Kerala and neighboring Karnataka.
  • D. Coorg
    Coorg, also known as Kodagu, is a scenic hill district in Karnataka, India, famed for its coffee plantations, lush forests, and mist-covered landscapes.
  • E. Munnar
    Munnar is a popular hill station in the Western Ghats of southern India, renowned for its sprawling tea plantations, cool climate, and scenic mountain landscapes.
  • 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_69bd43d6251c81909deecce3e6e9d69c completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd572402f481908151f7899bc96306 completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f8f66ac8190b719a653686c7258 completed March 20, 2026, 5:10 p.m.
Created at: March 20, 2026, 1:02 p.m.