Triple

T2870254
Position Surface form Disambiguated ID Type / Status
Subject Vicenza E63542 entity
Predicate twinnedWith P1072 FINISHED
Object Pforzheim E208654 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: Pforzheim | Statement: [Vicenza, twinnedWith, Pforzheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pforzheim
Context triple: [Vicenza, twinnedWith, Pforzheim]
  • A. Pforzheim chosen
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • B. Rastatt
    Rastatt is a historic town in southwestern Germany, known for its Baroque architecture and its role as the site of significant early 18th-century peace negotiations.
  • C. Albstadt
    Albstadt is a town in the Swabian Jura region of Baden-Württemberg, Germany, known for its textile industry, scenic hiking and cycling routes, and role as a regional economic center.
  • D. Schwäbisch Gmünd
    Schwäbisch Gmünd is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and long tradition of metalworking and jewelry craftsmanship.
  • E. Freudenstadt
    Freudenstadt is a spa and holiday town in southwestern Germany known for its large market square and location in the northern Black Forest.
  • 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_69ab4c42fb8c8190b36e161d47c03b81 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdfe2dcb48190a194253e733d14af completed March 7, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69b31a495fbc81909e40627a3feb9f42 completed March 12, 2026, 7:55 p.m.
Created at: March 6, 2026, 10:02 p.m.