Triple

T14006647
Position Surface form Disambiguated ID Type / Status
Subject County of Waldeck E336965 entity
Predicate hasRulerTitle P17756 FINISHED
Object Count of 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: Count of Waldeck | Statement: [County of Waldeck, hasRulerTitle, Count of Waldeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Count of Waldeck
Context triple: [County of Waldeck, hasRulerTitle, Count of Waldeck]
  • A. Count of Schwarzenberg
    Count of Schwarzenberg is a hereditary title of a prominent Bohemian noble family that rose to significant influence within the Habsburg Monarchy.
  • B. Graf zu Waldeck chosen
    Graf zu Waldeck is a noble title historically borne by members of the German princely House of Waldeck.
  • C. Prince of Waldeck
    The Prince of Waldeck was a German noble and military leader who commanded Allied forces against France during the late 17th century.
  • D. Count of Schaumburg-Lippe
    The Count of Schaumburg-Lippe was the hereditary ruler of the small German county of Schaumburg-Lippe, a minor principality within the Holy Roman Empire and later the German Confederation.
  • E. House of Waldeck
    The House of Waldeck was a German noble dynasty that ruled the small principality of Waldeck in what is now central Germany.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed327d88190a53af5768468a8eb completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbaca5fb48819090fff1fd22e8a15c completed May 6, 2026, 9:03 p.m.
Created at: April 9, 2026, 10:19 p.m.