Triple

T18986338
Position Surface form Disambiguated ID Type / Status
Subject Martim Moniz E464567 entity
Predicate near P350 FINISHED
Object Mouraria NE NERFINISHED

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: Mouraria | Statement: [Martim Moniz, near, Mouraria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mouraria
Context triple: [Martim Moniz, near, Mouraria]
  • A. Mouraria chosen
    Mouraria is a historic Lisbon neighborhood known for its multicultural character, narrow medieval streets, and deep ties to traditional fado music.
  • B. Marrangu
    Marrangu is a clan or dialect group within the Yolngu people of Arnhem Land in northern Australia, associated with the broader Yolngu Matha language family.
  • C. Mapusa
    Mapusa is a bustling commercial town in North Goa, India, known as a major market and transport hub near the popular beaches of the state.
  • D. Marromeu
    Marromeu is a town and district in central Mozambique known for its location along the Zambezi River and proximity to the Marromeu Buffalo Reserve.
  • E. Marudi
    Marudi is a small inland town in northern Sarawak, Malaysia, serving as an administrative and commercial hub for the surrounding Baram region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd008af48190a97ff1c6488edf1b completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d660835c8190bedd78590b3e0a7e completed April 20, 2026, 7:31 a.m.
Created at: April 10, 2026, 12:01 p.m.