Triple

T10630580
Position Surface form Disambiguated ID Type / Status
Subject Baixada Fluminense E250441 entity
Predicate containsAdministrativeUnit P3892 FINISHED
Object Mesquita E856564 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: Mesquita | Statement: [Baixada Fluminense, containsAdministrativeUnit, Mesquita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mesquita
Context triple: [Baixada Fluminense, containsAdministrativeUnit, Mesquita]
  • A. Mesquita chosen
    Mesquita is a municipality in the state of Rio de Janeiro, Brazil, situated within the densely populated urban area surrounding the city of Rio de Janeiro.
  • B. Mesquita
    Mesquita is a Portuguese-language surname of Iberian origin borne by various notable individuals across the Lusophone world.
  • C. Alamata
    Alamata is a town in northern Ethiopia that serves as a local commercial and administrative center in the southern part of the Tigray Region.
  • D. Bassel
    Bassel is an Arabic masculine given name commonly used in the Levant and other Arabic-speaking regions.
  • E. Madarihat
    Madarihat is a small town in West Bengal, India, known primarily as the main gateway and service hub for visitors to Jaldapara National Park.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6df93a2b88190a0f3a52b8e88f54f completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96bb4bbf08190994ea9123c0b2dab completed April 10, 2026, 9:29 p.m.
Created at: April 8, 2026, 9:01 p.m.