Triple

T14006638
Position Surface form Disambiguated ID Type / Status
Subject County of Waldeck E336965 entity
Predicate shortName P43 FINISHED
Object Waldeck E41198 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: Waldeck | Statement: [County of Waldeck, shortName, Waldeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waldeck
Context triple: [County of Waldeck, shortName, Waldeck]
  • A. Waldeck chosen
    Waldeck was a small German principality whose soldiers, like the Hessian troops, were hired out as auxiliaries to foreign powers in the 18th century.
  • B. Minna Waldeck
    Minna Waldeck was the wife of renowned German mathematician and scientist Carl Friedrich Gauss.
  • C. Ferdinand Sarrien
    Ferdinand Sarrien was a French Third Republic politician and statesman who served as Prime Minister and played a key role in the moderate republican movement.
  • D. Briand
    Briand is a French surname most notably borne by Aristide Briand, a prominent early 20th-century statesman and Nobel Peace Prize laureate.
  • E. Andrésy
    Andrésy is a suburban commune in north-central France, located in the Yvelines department within the Île-de-France region.
  • 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.