Triple

T9349307
Position Surface form Disambiguated ID Type / Status
Subject Limburg an der Lahn E224973 entity
Predicate locatedNear P294 FINISHED
Object Koblenz E196047 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: Koblenz | Statement: [Limburg an der Lahn, locatedNear, Koblenz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koblenz
Context triple: [Limburg an der Lahn, locatedNear, Koblenz]
  • A. Koblenz chosen
    Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
  • B. Mainz
    Mainz is a historic German city on the Rhine River known as a major ecclesiastical and political center of the Holy Roman Empire and today as the capital of the state of Rhineland-Palatinate.
  • C. Cologne
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • D. Mannheim
    Mannheim is a major city in southwestern Germany, known as an important industrial, commercial, and cultural center at the confluence of the Rhine and Neckar rivers.
  • E. Wuppertal
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • 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_69ca842abfd48190949d71c3b86eeba8 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4f1198b88190adc0b01f7c1be36e completed April 1, 2026, 5 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19f55c9c881909a315d10cea10834 completed April 4, 2026, 11:31 p.m.
Created at: March 30, 2026, 7:41 p.m.