Triple

T5095937
Position Surface form Disambiguated ID Type / Status
Subject 116th Panzer Division E114862 entity
Predicate notableLocation P3858 FINISHED
Object Aachen E43082 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: Aachen | Statement: [116th Panzer Division, notableLocation, Aachen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aachen
Context triple: [116th Panzer Division, notableLocation, Aachen]
  • A. Aachen chosen
    Aachen is a historic German city near the borders with Belgium and the Netherlands, renowned for its medieval cathedral, role as a coronation site for Holy Roman Emperors, and significance in both World Wars.
  • B. Trier
    Trier is a historic city in western Germany, renowned as one of the country’s oldest cities with extensive Roman ruins and medieval landmarks.
  • C. Neuss
    Neuss is a city in western Germany, near Düsseldorf, known as an administrative and commercial center with historical roots dating back to Roman times.
  • D. Maubeuge
    Maubeuge is a fortified industrial town in northern France near the Belgian border, historically significant for its strategic military position.
  • E. Neunkirchen
    Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
  • 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_69bd443fc49c819089629c00e311310c completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75652a8081908386718f1fdb1de3 completed March 20, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf70c59678819097aed5af25f36b66 completed March 22, 2026, 4:32 a.m.
Created at: March 20, 2026, 1:40 p.m.