Triple

T13825621
Position Surface form Disambiguated ID Type / Status
Subject Ludovicus Pius E332240 entity
Predicate deathPlace P21 FINISHED
Object Ingelheim E238373 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: Ingelheim | Statement: [Ludovicus Pius, deathPlace, Ingelheim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ingelheim
Context triple: [Ludovicus Pius, deathPlace, Ingelheim]
  • A. Ingelheim am Rhein chosen
    Ingelheim am Rhein is a town in western Germany on the Rhine River, known historically as an imperial residence of Charlemagne and today for its wine production and pharmaceutical industry.
  • B. Weinheim
    Weinheim is a historic town in southwestern Germany, known for its picturesque old town, twin castles, and location on the Bergstraße at the edge of the Odenwald.
  • C. Bensheim
    Bensheim is a historic town in southern Hesse, Germany, known for its wine-growing tradition and picturesque location on the Bergstraße at the edge of the Odenwald.
  • D. Heppenheim
    Heppenheim is a historic town in southwestern Germany, known for its picturesque old town, vineyards, and location on the Bergstraße at the edge of the Odenwald.
  • E. Walldorf
    Walldorf is a town in southwestern Germany best known as the headquarters of software giant SAP and for its strong economic base in the technology sector.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0295d2d48190b08eba0d805bd72d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a2df73c8190aeb6f472ac7ebeed completed May 8, 2026, 5:52 a.m.
Created at: April 9, 2026, 10:13 p.m.