Triple

T11099184
Position Surface form Disambiguated ID Type / Status
Subject Camille Jordan E262458 entity
Predicate givenName P17 FINISHED
Object Ennemond
Ennemond is a given name notably borne by the French mathematician Camille Jordan.
 E904576 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: Ennemond | Statement: [Camille Jordan, givenName, Ennemond]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ennemond
Context triple: [Camille Jordan, givenName, Ennemond]
  • A. Alaemon
    Alaemon is a small genus of larks known for their ground-dwelling habits and adaptation to arid and semi-arid environments.
  • B. Alvarus
    Alvarus is a Latinized variant of the given name Alvar, historically used in medieval and ecclesiastical contexts.
  • C. Naberius
    Naberius is the main demonic antagonist in the film "I, Frankenstein," depicted as a powerful prince of demons seeking to harness reanimation technology for his own dark purposes.
  • D. Gothardus
    Gothardus is a Latinized form of the name Gotthard, most commonly associated with Saint Gotthard of Hildesheim, an 11th-century German bishop and saint.
  • E. Ursem
    Ursem is a village in the Dutch province of North Holland, known for its rural character and traditional polder landscape.
  • 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: Ennemond
Triple: [Camille Jordan, givenName, Ennemond]
Generated description
Ennemond is a given name notably borne by the French mathematician Camille Jordan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ennemond
Target entity description: Ennemond is a given name notably borne by the French mathematician Camille Jordan.
  • A. Alaemon
    Alaemon is a small genus of larks known for their ground-dwelling habits and adaptation to arid and semi-arid environments.
  • B. Alvarus
    Alvarus is a Latinized variant of the given name Alvar, historically used in medieval and ecclesiastical contexts.
  • C. Naberius
    Naberius is the main demonic antagonist in the film "I, Frankenstein," depicted as a powerful prince of demons seeking to harness reanimation technology for his own dark purposes.
  • D. Gothardus
    Gothardus is a Latinized form of the name Gotthard, most commonly associated with Saint Gotthard of Hildesheim, an 11th-century German bishop and saint.
  • E. Ursem
    Ursem is a village in the Dutch province of North Holland, known for its rural character and traditional polder landscape.
  • 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_69d6aa9a40d88190a373e2c7e48285db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79a0c46308190889b94c23ebaca62 completed April 9, 2026, 12:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3e7eca9bc8190b43bae081d97d804 completed April 18, 2026, 8:22 p.m.
NEDg Description generation batch_69e3f2cbb4708190a328cff473104d14 completed April 18, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69e3f497a01881909d1dae70a02e5f97 completed April 18, 2026, 9:16 p.m.
Created at: April 8, 2026, 9:27 p.m.