Triple

T1395596
Position Surface form Disambiguated ID Type / Status
Subject Battle of the Ruhr E30657 entity
Predicate location P40 FINISHED
Object Ruhr E80553 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: Ruhr | Statement: [Battle of the Ruhr, location, Ruhr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruhr
Context triple: [Battle of the Ruhr, location, Ruhr]
  • A. Ruhr chosen
    The Ruhr is a river in western Germany that flows through the Ruhr industrial region before joining the Rhine.
  • B. Lippe
    Lippe is a historical region in northwestern Germany that once formed a small principality and later a Free State within the German Reich.
  • C. Lippe
    The Lippe is a river in western Germany that flows through North Rhine-Westphalia and is a right-bank tributary of the Rhine.
  • 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_69a498fd4e408190bd73eca30ea9754c completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c37fd6e0819084d610ef041db3af completed March 1, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293ab8508190ac321c898cd3df39 completed March 8, 2026, 7:46 a.m.
Created at: March 1, 2026, 7:59 p.m.