Triple

T3089424
Position Surface form Disambiguated ID Type / Status
Subject Argenteuil E64453 entity
Predicate hasTwinTown P919 FINISHED
Object Dessau-Roßlau E102721 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: Dessau-Roßlau | Statement: [Argenteuil, hasTwinTown, Dessau-Roßlau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau-Roßlau
Context triple: [Argenteuil, hasTwinTown, Dessau-Roßlau]
  • A. Dessau chosen
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • B. Oranienburg
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • C. Degendorf
    Degendorf is a locality within the Bavarian town and district of Lichtenfels in Germany.
  • D. Fürstenwalde
    Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
  • E. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • 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_69ad857c97d88190b26f9b1c90839c77 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada20b99a4819090c3d3e08ed556ad completed March 8, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdbd9a9c8190b1135a4120ac0c6b completed March 14, 2026, 2:53 a.m.
Created at: March 8, 2026, 3:03 p.m.