Triple

T12331225
Position Surface form Disambiguated ID Type / Status
Subject Mujeres riendo E293963 entity
Predicate wasOriginallyLocatedNear P54388 FINISHED
Object Madrid E4617 NE FINISHED

How this triple was built (3 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: Madrid | Statement: [Mujeres riendo, wasOriginallyLocatedNear, Madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madrid
Context triple: [Mujeres riendo, wasOriginallyLocatedNear, Madrid]
  • A. Madrid
    Madrid is a municipality in the Cundinamarca department of Colombia, located near Bogotá and known for its floriculture and agricultural production.
  • B. Madrid
    Madrid is a coastal municipality in the Philippine province of Surigao del Sur on the island of Mindanao.
  • C. Madrid chosen
    Madrid is the capital and largest city of Spain, renowned for its rich cultural heritage, historic architecture, and vibrant arts and nightlife scenes.
  • D. Madri
    Madri is a princess from the Mahabharata epic, known as the second wife of King Pandu and the mother of the twins Nakula and Sahadeva.
  • E. Seville
    Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: wasOriginallyLocatedNear
Context triple: [Mujeres riendo, wasOriginallyLocatedNear, Madrid]
  • A. locatedNearFormer
    Indicates that one entity is situated close to another entity that previously occupied a nearby or the same location.
  • B. formerlyLocatedOn
    Indicates that an entity was once located on or situated upon another entity, but is no longer in that position.
  • C. locatedInOrNearModernSettlement chosen
    Indicates that something is situated within or in close proximity to a present-day town, city, or other populated settlement.
  • D. locatedInOldCity
    Indicates that an entity is situated within the boundaries of an old or historic part of a city.
  • E. historicalLocationOf
    Indicates that a place served as a significant site or setting for an entity during a particular historical period or event.
  • F. None of above.

Provenance (4 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f634ee08190b4f533505d402219 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a7c2b0081909994ea88683a39f4 completed May 2, 2026, 4:46 p.m.
PD Predicate disambiguation batch_69d93ec5be788190b82d2edc6a0f1095 completed April 10, 2026, 6:17 p.m.
Created at: April 8, 2026, 9:53 p.m.