Triple

T16666483
Position Surface form Disambiguated ID Type / Status
Subject Eudeve E404994 entity
Predicate hasAlternativeName P39 FINISHED
Object Hegü
Hegü is an alternative name for the Eudeve language, an indigenous Uto-Aztecan language historically spoken in northern Mexico.
 E1227589 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: Hegü | Statement: [Eudeve, hasAlternativeName, Hegü]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hegü
Context triple: [Eudeve, hasAlternativeName, Hegü]
  • A. 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.
  • B. Hilla
    Hilla is the nickname of Hilla Rebay, a German-born abstract art curator and painter best known for co-founding and shaping the early collection of the Solomon R. Guggenheim Museum.
  • C. Hage
    Hage is the given name of Hage Geingob, the late president of Namibia and a prominent figure in the country’s post-independence politics.
  • D. Huny
    Huny is an alternative transliteration of Huni, an ancient Egyptian pharaoh of the Third Dynasty.
  • E. Haghi
    Haghi is a masterful and manipulative criminal mastermind and spymaster, best known as the primary antagonist in Fritz Lang’s silent espionage film "Spies."
  • 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: Hegü
Triple: [Eudeve, hasAlternativeName, Hegü]
Generated description
Hegü is an alternative name for the Eudeve language, an indigenous Uto-Aztecan language historically spoken in northern Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hegü
Target entity description: Hegü is an alternative name for the Eudeve language, an indigenous Uto-Aztecan language historically spoken in northern Mexico.
  • A. 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.
  • B. Hilla
    Hilla is the nickname of Hilla Rebay, a German-born abstract art curator and painter best known for co-founding and shaping the early collection of the Solomon R. Guggenheim Museum.
  • C. Hage
    Hage is the given name of Hage Geingob, the late president of Namibia and a prominent figure in the country’s post-independence politics.
  • D. Huny
    Huny is an alternative transliteration of Huni, an ancient Egyptian pharaoh of the Third Dynasty.
  • E. Haghi
    Haghi is a masterful and manipulative criminal mastermind and spymaster, best known as the primary antagonist in Fritz Lang’s silent espionage film "Spies."
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37c9cd7ec819084aa9b2830874bf5 completed April 18, 2026, 12:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a32988c8190a671a4cbd829047a completed May 10, 2026, 1:37 p.m.
NEDg Description generation batch_6a008aed0bfc8190886b6a2e08a885b9 completed May 10, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_6a008bc0e57c8190838ec383f2a1b52c completed May 10, 2026, 1:44 p.m.
Created at: April 10, 2026, 5:18 a.m.