Triple

T11079671
Position Surface form Disambiguated ID Type / Status
Subject Kindelán Orestes E261956 entity
Predicate familyName P18 FINISHED
Object Kindelán
Kindelán is a Spanish surname most notably associated with figures in military and political history.
 E903718 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: Kindelán | Statement: [Kindelán Orestes, familyName, Kindelán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kindelán
Context triple: [Kindelán Orestes, familyName, Kindelán]
  • A. Le Sépey
    Le Sépey is a small village in the canton of Vaud, Switzerland, situated in the Alps and serving as a local stop on the regional railway network.
  • B. Kaleibar
    Kaleibar is a small historic city in northwestern Iran known for its mountainous landscapes and proximity to the Babak Castle fortress.
  • C. Tegüder
    Tegüder (also known as Ahmad Tegüder) was a 13th-century Ilkhanid ruler of Persia who converted to Islam and briefly reigned as a Mongol khan.
  • D. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • E. Marandellas
    Marandellas is the former colonial-era name of Marondera, a town in eastern Zimbabwe known as an agricultural and educational 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: Kindelán
Triple: [Kindelán Orestes, familyName, Kindelán]
Generated description
Kindelán is a Spanish surname most notably associated with figures in military and political history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kindelán
Target entity description: Kindelán is a Spanish surname most notably associated with figures in military and political history.
  • A. Le Sépey
    Le Sépey is a small village in the canton of Vaud, Switzerland, situated in the Alps and serving as a local stop on the regional railway network.
  • B. Kaleibar
    Kaleibar is a small historic city in northwestern Iran known for its mountainous landscapes and proximity to the Babak Castle fortress.
  • C. Tegüder
    Tegüder (also known as Ahmad Tegüder) was a 13th-century Ilkhanid ruler of Persia who converted to Islam and briefly reigned as a Mongol khan.
  • D. Dovadola
    Dovadola is a small Italian town and municipality in the Emilia-Romagna region, known for its historic center and scenic location in the Apennine foothills.
  • E. Marandellas
    Marandellas is the former colonial-era name of Marondera, a town in eastern Zimbabwe known as an agricultural and educational 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_69d6aa9983c08190b0ef61603b69feac completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7999603948190934bca3a9151d726 completed April 9, 2026, 12:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e77a78288190aa76912e0fa821b5 completed April 18, 2026, 8:20 p.m.
NEDg Description generation batch_69e3f2c889dc81909a04c1db0509e3d9 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f4746dbc8190a0e28202ad5e6b4f completed April 18, 2026, 9:15 p.m.
Created at: April 8, 2026, 9:27 p.m.