Triple

T12816957
Position Surface form Disambiguated ID Type / Status
Subject Tübingen E306426 entity
Predicate locatedOnRiver 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, locatedOnRiver, Neckar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neckar
Context triple: [Tübingen, locatedOnRiver, 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. River Iller
    The River Iller is a major river in southern Germany that flows through the Allgäu region and joins the Danube near Ulm.
  • D. 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.
  • E. 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.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9d00088190ac0f5d60e1de7a7c completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbac73848481909303e833041ebc90 completed May 6, 2026, 9:02 p.m.
Created at: April 9, 2026, 5:31 p.m.