Triple

T4658105
Position Surface form Disambiguated ID Type / Status
Subject Stadtholder of Kniphausen E102457 entity
Predicate hasSeat P3522 FINISHED
Object Kniphausen
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
 E457422 NE FINISHED

How this triple was built (4 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: Kniphausen | Statement: [Stadtholder of Kniphausen, hasSeat, Kniphausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kniphausen
Context triple: [Stadtholder of Kniphausen, hasSeat, Kniphausen]
  • A. Lacedelli
    Lacedelli is an Italian surname most notably associated with Lino Lacedelli, one of the first climbers to reach the summit of K2.
  • B. Gaspra
    Gaspra is a seaside resort town on the southern coast of Crimea, known for its mild climate, beaches, and historic landmarks such as the Swallow's Nest castle.
  • C. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • D. Michell
    Michell is a given name and surname that functions as a variant spelling of Mitchell.
  • E. Kopervik
    Kopervik is a coastal town in Rogaland county, Norway, situated on the island of Karmøy and serving as an important local commercial and administrative center.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kniphausen
Triple: [Stadtholder of Kniphausen, hasSeat, Kniphausen]
Generated description
Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kniphausen
Target entity description: Kniphausen is a historical territory in present-day Germany that once functioned as a small semi-independent lordship under various regional powers.
  • A. Lacedelli
    Lacedelli is an Italian surname most notably associated with Lino Lacedelli, one of the first climbers to reach the summit of K2.
  • B. Gaspra
    Gaspra is a seaside resort town on the southern coast of Crimea, known for its mild climate, beaches, and historic landmarks such as the Swallow's Nest castle.
  • C. Kaiten
    Kaiten was a Japanese warship that took part in the late-19th-century Boshin War naval engagements, including the Battle of Hakodate.
  • D. Michell
    Michell is a given name and surname that functions as a variant spelling of Mitchell.
  • E. Kopervik
    Kopervik is a coastal town in Rogaland county, Norway, situated on the island of Karmøy and serving as an important local commercial and administrative center.
  • F. None of above. chosen

Provenance (5 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_69bd43d823288190952279faa0d1d066 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63271a548190bd9662b69a45d9a5 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaf5a0988190b097ef71301aebbe completed March 21, 2026, 1:57 a.m.
NEDg Description generation batch_69bdfc0964c881909e6b98a1c8ea747f completed March 21, 2026, 2:01 a.m.
NED2 Entity disambiguation (via description) batch_69bdfce1be788190ae3418df301e5136 completed March 21, 2026, 2:05 a.m.
Created at: March 20, 2026, 1:15 p.m.