Triple

T13296442
Position Surface form Disambiguated ID Type / Status
Subject Edith Holländer E316694 entity
Predicate residence P75 FINISHED
Object Aachen E43082 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: Aachen | Statement: [Edith Holländer, residence, Aachen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aachen
Context triple: [Edith Holländer, residence, Aachen]
  • A. Aachen chosen
    Aachen is a historic German city near the borders with Belgium and the Netherlands, renowned for its medieval cathedral, role as a coronation site for Holy Roman Emperors, and significance in both World Wars.
  • B. Trier
    Trier is a historic city in western Germany, renowned as one of the country’s oldest cities with extensive Roman ruins and medieval landmarks.
  • C. Neuss
    Neuss is a city in western Germany, near Düsseldorf, known as an administrative and commercial center with historical roots dating back to Roman times.
  • D. Maubeuge
    Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
  • E. Neunkirchen
    Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99079c8508190b6208db9affcbc0e completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7266832a881909403c4d3cbe1edec completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:28 p.m.