Triple

T561516
Position Surface form Disambiguated ID Type / Status
Subject Rhine E13461 entity
Predicate flowsThroughCity P10456 FINISHED
Object Mainz E188859 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: Mainz | Statement: [Rhine, flowsThroughCity, Mainz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mainz
Context triple: [Rhine, flowsThroughCity, Mainz]
  • A. Mainz chosen
    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.
  • B. 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.
  • C. Kaiserslautern
    Kaiserslautern is a city in southwestern Germany known for its historic old town, technical university, and prominent football club 1. FC Kaiserslautern.
  • D. 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.
  • E. Ludwigshafen am Rhein
    Ludwigshafen am Rhein is an industrial city in southwestern Germany on the Rhine River, best known as the headquarters of the chemical company BASF.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d28af148190acad3cfb809ff2f2 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad8a8f35d48190a18cf924bf5f9e45 completed March 8, 2026, 2:41 p.m.
Created at: March 1, 2026, 7:32 p.m.