Triple

T715511
Position Surface form Disambiguated ID Type / Status
Subject Hesse E14304 entity
Predicate containsCity P294 FINISHED
Object Darmstadt E107304 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: Darmstadt | Statement: [Hesse, containsCity, Darmstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darmstadt
Context triple: [Hesse, containsCity, Darmstadt]
  • A. Darmstadt chosen
    Darmstadt is a city in the German state of Hesse known for its historical ties to the Grand Duchy of Hesse and its role as a center of science, technology, and Art Nouveau culture.
  • B. Karlsruhe
    Karlsruhe is a major city in southwestern Germany best known as the seat of the country’s highest courts and a central hub of German constitutional jurisprudence.
  • C. Wiesbaden
    Wiesbaden is a historic spa city in western Germany known for its thermal springs, elegant architecture, and role as a regional administrative and cultural center.
  • D. Kaiserslautern
    Kaiserslautern is a city in southwestern Germany known for its historic old town, technical university, and prominent football club 1. FC Kaiserslautern.
  • E. Mannheim
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • 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_69a4934a36e081909e7abef98b898a4e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a574b4d881908b6d0be386081efd completed March 1, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69aeb39a387c8190b5c1f4876532e376 completed March 9, 2026, 11:48 a.m.
Created at: March 1, 2026, 7:37 p.m.