Triple

T11759666
Position Surface form Disambiguated ID Type / Status
Subject Graf zu Waldeck E279618 entity
Predicate titleInGerman P6492 FINISHED
Object Graf zu Waldeck E279618 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: Graf zu Waldeck | Statement: [Graf zu Waldeck, titleInGerman, Graf zu Waldeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graf zu Waldeck
Context triple: [Graf zu Waldeck, titleInGerman, Graf zu Waldeck]
  • A. Graf zu Waldeck chosen
    Graf zu Waldeck is a noble title historically borne by members of the German princely House of Waldeck.
  • B. Lord of Lippe
    The Lord of Lippe was the medieval noble title held by the rulers of the small German territory of Lippe before it was elevated to a county.
  • C. Dinkelscherben
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • D. Saal an der Saale
    Saal an der Saale is a small municipality in northern Bavaria, Germany, situated along the Franconian Saale River.
  • E. Land van Altena
    Land van Altena is a historical region in the northern part of the Dutch province of North Brabant, known for its rural landscape and position along major rivers such as the Waal and Merwede.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a5220f148190ae60d1941a579ab6 completed April 10, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69f01a3dfd1081908221c8061931282b completed April 28, 2026, 2:23 a.m.
Created at: April 8, 2026, 9:41 p.m.