Triple

T16350733
Position Surface form Disambiguated ID Type / Status
Subject Hage Geingob E397054 entity
Predicate givenName P17 FINISHED
Object 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.
 E1208625 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: Hage | Statement: [Hage Geingob, givenName, Hage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hage
Context triple: [Hage Geingob, givenName, Hage]
  • A. 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."
  • B. Hagaz
    Hagaz is a town in Eritrea’s Anseba region, known primarily as an agricultural and local administrative center.
  • C. Hain
    Hain is an ancient, central world in Ursula K. Le Guin’s Hainish Cycle, often portrayed as the cradle of human-like civilizations across the galaxy.
  • D. Haise
    Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
  • E. Haya
    The Haya are a Bantu-speaking ethnic group of northwestern Tanzania, known for their advanced precolonial ironworking and intensive banana-based agriculture around Lake Victoria.
  • 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: Hage
Triple: [Hage Geingob, givenName, Hage]
Generated description
Hage is the given name of Hage Geingob, the late president of Namibia and a prominent figure in the country’s post-independence politics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hage
Target entity description: Hage is the given name of Hage Geingob, the late president of Namibia and a prominent figure in the country’s post-independence politics.
  • A. 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."
  • B. Hagaz
    Hagaz is a town in Eritrea’s Anseba region, known primarily as an agricultural and local administrative center.
  • C. Hain
    Hain is an ancient, central world in Ursula K. Le Guin’s Hainish Cycle, often portrayed as the cradle of human-like civilizations across the galaxy.
  • D. Haise
    Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
  • E. Haya
    The Haya are a Bantu-speaking ethnic group of northwestern Tanzania, known for their advanced precolonial ironworking and intensive banana-based agriculture around Lake Victoria.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2facb37d0819093fe45446f1e79c1 completed April 18, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002db6375c81908c64dbe2bc987b1a completed May 10, 2026, 7:03 a.m.
NEDg Description generation batch_6a00304d7c888190a018d865eb51f0a0 completed May 10, 2026, 7:14 a.m.
NED2 Entity disambiguation (via description) batch_6a00309ceba88190a982b439a1e72e78 completed May 10, 2026, 7:15 a.m.
Created at: April 10, 2026, 5:07 a.m.