Triple

T6679718
Position Surface form Disambiguated ID Type / Status
Subject Tübingen E151945 entity
Predicate hasRiver P165 FINISHED
Object Neckar E79602 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: Neckar | Statement: [Tübingen, hasRiver, Neckar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neckar
Context triple: [Tübingen, hasRiver, Neckar]
  • A. Neckar chosen
    The Neckar is a significant river in southwestern Germany that flows through cities like Stuttgart and Heidelberg before joining the Rhine.
  • B. Kinzig
    The Kinzig is a river in southwestern Germany that flows through the Black Forest region before joining the Rhine.
  • C. Regnitz
    The Regnitz is a river in the German state of Bavaria that flows through cities such as Erlangen and Bamberg before joining the Main River.
  • D. High Rhine
    The High Rhine is a stretch of the Rhine River in Central Europe, flowing swiftly between Lake Constance and Basel and forming part of the border between Germany and Switzerland.
  • E. Jagst
    The Jagst is a river in Baden-Württemberg, Germany, known as one of the major right-bank tributaries of the Neckar and flowing through a largely rural, scenic landscape.
  • 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b11df8d88190bf19fcb4e7a0bdb3 completed March 27, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769ddf9e08190b64216fa37d6ca19 completed March 28, 2026, 5:40 a.m.
Created at: March 27, 2026, 2:03 p.m.