Triple

T16254444
Position Surface form Disambiguated ID Type / Status
Subject Camorta E394592 entity
Predicate hasNearbyIsland P970 FINISHED
Object Teressa E109218 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: Teressa | Statement: [Camorta, hasNearbyIsland, Teressa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teressa
Context triple: [Camorta, hasNearbyIsland, Teressa]
  • A. Teressa chosen
    Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
  • B. Teresa
    Teresa is the central protagonist of the play "The Memory of Water," around whom the story’s emotional and familial conflicts revolve.
  • C. Teresa
    Teresa is a central figure in Carlos Fuentes’s novel "The Death of Artemio Cruz," representing both a pivotal love interest and a symbol of the social and emotional conflicts surrounding the protagonist.
  • D. Teresa
    Teresa is a feminine given name commonly used in various cultures, often associated with notable religious and historical figures.
  • E. Teresa
    Teresa is a municipality in the province of Rizal in the Philippines, known for its residential communities and proximity to Metro Manila.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24599861881908b9235f005d80a96 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b1e22c8190bddca67661121c2d completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:04 a.m.