Triple

T7147165
Position Surface form Disambiguated ID Type / Status
Subject Mahé E166597 entity
Predicate partOf P40 FINISHED
Object Mahé district E166597 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: Mahé district | Statement: [Mahé, partOf, Mahé district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mahé district
Context triple: [Mahé, partOf, Mahé district]
  • A. Mahé chosen
    Mahé is a former French colonial settlement on the Malabar Coast of India, now a small coastal town and district enclave of the Union Territory of Puducherry.
  • B. Mahé
    Mahé is the largest and most populous island of Seychelles, home to the nation’s capital, Victoria, and its main economic and cultural center.
  • C. Praslin
    Praslin is the second-largest island of Seychelles, renowned for its white-sand beaches, lush tropical forests, and the UNESCO-listed Vallée de Mai nature reserve.
  • D. Bentota
    Bentota is a popular coastal resort town in southwestern Sri Lanka, known for its beaches, river, and water sports tourism.
  • E. Dhives Akuru
    Dhives Akuru is an ancient script formerly used to write the Maldivian Dhivehi language before its replacement by the modern Thaana script.
  • 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_69c68886779c8190a8e3fbabffe68253 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7d4f3388190941f03fd80b0c223 completed March 27, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ada12a848190b6e98e0b1a258c17 completed March 28, 2026, 10:29 a.m.
Created at: March 27, 2026, 2:46 p.m.