Triple

T15806290
Position Surface form Disambiguated ID Type / Status
Subject Nancowry Islands E383224 entity
Predicate hasMajorSettlement P316 FINISHED
Object Kamorta E339346 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: Kamorta | Statement: [Nancowry Islands, hasMajorSettlement, Kamorta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kamorta
Context triple: [Nancowry Islands, hasMajorSettlement, Kamorta]
  • A. Kamorta chosen
    Kamorta is a significant inhabited island and settlement in India’s Nicobar archipelago, known for its strategic location and indigenous Nicobarese communities.
  • B. Kamiros
    Kamiros is an ancient city and archaeological site on the northwest coast of Rhodes, known for its well-preserved Hellenistic ruins and grid-planned layout.
  • C. Lothagam
    Lothagam is an archaeological and geological site in northern Kenya known for its ancient human burials and prominent rock formations along the western shore of Lake Turkana.
  • D. Karnut
    Karnut is a rural village located within Armenia's Shirak Province.
  • E. Lanaken
    Lanaken is a municipality in the Belgian province of Limburg, known for its proximity to Maastricht and its mix of residential areas, industry, and natural 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b52682548190998d8b6a08982877 completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff998fa5588190b28efc2f342405aa completed May 9, 2026, 8:31 p.m.
Created at: April 10, 2026, 4:48 a.m.