Triple

T7439976
Position Surface form Disambiguated ID Type / Status
Subject Marovo E171721 entity
Predicate hasNeighbouringLanguage P16383 FINISHED
Object Gizo E534100 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: Gizo | Statement: [Marovo, hasNeighbouringLanguage, Gizo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gizo
Context triple: [Marovo, hasNeighbouringLanguage, Gizo]
  • A. Gizo chosen
    Gizo is a small island town in the Solomon Islands known as an administrative and commercial hub in the western part of the country and a popular base for diving and marine tourism.
  • B. Gugino
    Gugino is the surname of American actress Carla Gugino, known for her versatile roles in film and television.
  • C. Girga
    Girga is an ancient town in Upper Egypt, historically significant as a regional center along the Nile.
  • D. Totegegie
    Totegegie is a small, remote island in French Polynesia known primarily for its airport, which serves as the main air gateway to the Gambier Islands.
  • E. Gedo
    Gedo is a region in southwestern Somalia known for its strategic location bordering Kenya and Ethiopia and its role within the federal state of Jubaland.
  • 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_69c68a64228c8190affaec2a8127ce7b completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f34c28648190a426b5d7623b41e8 completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c82791ff2c81909967f145d24ff036 completed March 28, 2026, 7:10 p.m.
Created at: March 27, 2026, 3:13 p.m.