Triple

T6492526
Position Surface form Disambiguated ID Type / Status
Subject Ferdinand de Marsin E148075 entity
Predicate placeOfBirth P1 FINISHED
Object Liège E142916 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: Liège | Statement: [Ferdinand de Marsin, placeOfBirth, Liège]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liège
Context triple: [Ferdinand de Marsin, placeOfBirth, Liège]
  • A. Liège chosen
    Liège is a major city in eastern Belgium known for its industrial heritage, vibrant cultural scene, and position along the Meuse River.
  • B. Namur
    Namur is a historic Belgian city and the capital of Wallonia, located at the confluence of the Meuse and Sambre rivers.
  • C. Braine-l'Alleud
    Braine-l'Alleud is a municipality in Walloon Brabant, Belgium, known for encompassing much of the historic Waterloo battlefield.
  • D. Nivelles
    Nivelles is a historic town in present-day Belgium known for its medieval architecture, including the Romanesque Collegiate Church of Saint Gertrude.
  • E. Binche
    Binche is a historic town in the Walloon region of Belgium, renowned for its well-preserved medieval architecture and its UNESCO-recognized Carnival of Binche.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a9bf9208190b0957eda06ed3d65 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c6ec470819088f16fd762d3c7d7 completed March 28, 2026, 9:16 a.m.
Created at: March 22, 2026, 4:53 p.m.