Triple

T20066672
Position Surface form Disambiguated ID Type / Status
Subject Greater Tehran E499624 entity
Predicate contains P35 FINISHED
Object Malard 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: Malard | Statement: [Greater Tehran, contains, Malard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malard
Context triple: [Greater Tehran, contains, Malard]
  • A. Malard chosen
    Malard is a city in Tehran Province, Iran, known as an urban and administrative center within the Malard County region.
  • B. Mauzy
    Mauzy is the surname of American actress Mackenzie Mauzy, known for her roles in television and film.
  • C. Marly
    Marly is a French locality historically associated with royal architecture and landscape design, notably linked to the works of architect Jules Hardouin-Mansart.
  • D. Meldoise
    Meldoise is the French demonym for an inhabitant of the town of Meaux in the Île-de-France region.
  • E. Murra
    Murra is a small town in northern Nicaragua that serves as one of the principal urban centers of the Nueva Segovia Department.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66379f2cc81908f13a7b216878f12 completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.