Triple

T9507945
Position Surface form Disambiguated ID Type / Status
Subject Götterdämmerung E229316 entity
Predicate featuresCharacter P626 FINISHED
Object Hagen E571843 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: Hagen | Statement: [Götterdämmerung, featuresCharacter, Hagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hagen
Context triple: [Götterdämmerung, featuresCharacter, Hagen]
  • A. Hagen
    Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
  • B. Hagen chosen
    Hagen is a surname of German origin borne by various notable individuals across fields such as music, sports, and academia.
  • C. Gescher
    Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
  • D. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • E. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9855c5e48190a7d8d39b6d601679 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190d2397081909127cb356b956f35 completed April 4, 2026, 10:29 p.m.
Created at: March 30, 2026, 7:57 p.m.