Triple

T7064833
Position Surface form Disambiguated ID Type / Status
Subject Blaustein E164318 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Neu-Ulm E177294 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: Neu-Ulm | Statement: [Blaustein, hasNeighbouringMunicipality, Neu-Ulm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neu-Ulm
Context triple: [Blaustein, hasNeighbouringMunicipality, Neu-Ulm]
  • A. Neu-Ulm chosen
    Neu-Ulm is a Bavarian town in southern Germany located across the Danube River from the city of Ulm, forming a closely linked urban area with it.
  • B. Landsberg am Lech
    Landsberg am Lech is a historic Bavarian town in southern Germany known for its medieval old town, picturesque setting on the Lech River, and its association with the nearby Landsberg Prison.
  • C. Backnang
    Backnang is a town in the German state of Baden-Württemberg, located northeast of Stuttgart and known for its historical center and role as a regional industrial and commuter hub.
  • D. Kaufbeuren
    Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
  • E. Rosenheim
    Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
  • 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_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e45e80e08190bb1a79a6026d2cd5 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69cc638e62608190958e90b07138a1cc completed April 1, 2026, 12:15 a.m.
Created at: March 27, 2026, 2:39 p.m.