Triple

T21346907
Position Surface form Disambiguated ID Type / Status
Subject A4 motorway E526362 entity
Predicate passesNear P416 FINISHED
Object Metz 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: Metz | Statement: [A4 motorway, passesNear, Metz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metz
Context triple: [A4 motorway, passesNear, Metz]
  • A. Metz
    Metz is a small rural village located in Vernon County in western Missouri, United States.
  • B. Metz chosen
    Metz is a historic city in northeastern France known for its Gothic Saint-Stephen Cathedral, Roman and medieval heritage, and role as the capital of the Moselle department in the Grand Est region.
  • C. Metz
    Metz is a German-origin surname borne by various notable individuals, including American actress Chrissy Metz.
  • D. Metz Métropole
    Metz Métropole is an intercommunal metropolitan authority in northeastern France that coordinates urban planning, economic development, and public services for Metz and its surrounding municipalities.
  • E. Maubeuge
    Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
  • 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_69e0b51cd5cc81909ac1187971e8a8ad completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5ba8f1c8819089c5d753876b44d5 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 4:55 p.m.