Triple

T15207610
Position Surface form Disambiguated ID Type / Status
Subject Hugo Häring E363428 entity
Predicate placeOfDeath P21 FINISHED
Object Göppingen E751532 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: Göppingen | Statement: [Hugo Häring, placeOfDeath, Göppingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Göppingen
Context triple: [Hugo Häring, placeOfDeath, Göppingen]
  • A. Göppingen chosen
    Göppingen is a town in the German state of Baden-Württemberg known as an industrial and administrative center in the Filstal valley near Stuttgart.
  • B. Pforzheim
    Pforzheim is a city in southwestern Germany, historically known for its jewelry and watchmaking industry and its heavy destruction during World War II.
  • C. 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.
  • D. Reutlingen
    Reutlingen is a city in southwestern Germany known for its location at the foot of the Swabian Jura and its well-preserved medieval old town.
  • E. Heilbronn
    Heilbronn is a city in the German state of Baden-Württemberg known for its industrial base, wine production, and role as a regional economic and educational hub.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b8e2788190bd1831762e4181ae completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c2d21348190a8045cf1847396e0 completed May 9, 2026, 3:01 p.m.
Created at: April 10, 2026, 3:11 a.m.