Triple

T13565515
Position Surface form Disambiguated ID Type / Status
Subject Geremi Njitap E324023 entity
Predicate givenName P17 FINISHED
Object Geremi
Geremi is a retired Cameroonian footballer best known for his versatility as a defender and midfielder and for his successful spells at clubs like Real Madrid and Chelsea, as well as his long international career with Cameroon.
 E1047166 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: Geremi | Statement: [Geremi Njitap, givenName, Geremi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Geremi
Context triple: [Geremi Njitap, givenName, Geremi]
  • A. Gemer
    Gemer is a historical and geographical region in southern Slovakia known for its mining heritage, medieval castles, and karst landscapes.
  • B. Gery
    Gery is a spelling variant of the given name Gerry, typically used as a personal name.
  • C. Geri
    Geri is a common diminutive or nickname for the given name Geraldine.
  • D. Geri
    Geri is one of the two mythological wolves who accompany the Norse god Odin.
  • E. Geremek
    Geremek is a Polish surname most notably associated with Bronisław Geremek, a prominent historian, Solidarity activist, and post-communist foreign minister of Poland.
  • 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: Geremi
Triple: [Geremi Njitap, givenName, Geremi]
Generated description
Geremi is a retired Cameroonian footballer best known for his versatility as a defender and midfielder and for his successful spells at clubs like Real Madrid and Chelsea, as well as his long international career with Cameroon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Geremi
Target entity description: Geremi is a retired Cameroonian footballer best known for his versatility as a defender and midfielder and for his successful spells at clubs like Real Madrid and Chelsea, as well as his long international career with Cameroon.
  • A. Gemer
    Gemer is a historical and geographical region in southern Slovakia known for its mining heritage, medieval castles, and karst landscapes.
  • B. Gery
    Gery is a spelling variant of the given name Gerry, typically used as a personal name.
  • C. Geri
    Geri is a common diminutive or nickname for the given name Geraldine.
  • D. Geri
    Geri is one of the two mythological wolves who accompany the Norse god Odin.
  • E. Geremek
    Geremek is a Polish surname most notably associated with Bronisław Geremek, a prominent historian, Solidarity activist, and post-communist foreign minister of Poland.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00cecd48190a9a2caff3d424817 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75daf1bfc8190bf22eb9ef242f54f completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75f9c6a8881908a6df0a9a4bbc7ab completed May 3, 2026, 2:45 p.m.
NED2 Entity disambiguation (via description) batch_69f7601770ac8190a03be23cfe66d5d1 completed May 3, 2026, 2:47 p.m.
Created at: April 9, 2026, 9:48 p.m.