Triple

T6389544
Position Surface form Disambiguated ID Type / Status
Subject Lee Garmes E143785 entity
Predicate familyName P18 FINISHED
Object Garmes
Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
 E595409 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: Garmes | Statement: [Lee Garmes, familyName, Garmes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Garmes
Context triple: [Lee Garmes, familyName, Garmes]
  • A. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • B. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • C. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • D. Éveux
    Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
  • E. Cigales
    Cigales is a small town in the province of Valladolid, Spain, known historically as a royal residence and for its wine production.
  • 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: Garmes
Triple: [Lee Garmes, familyName, Garmes]
Generated description
Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Garmes
Target entity description: Garmes is a surname most notably associated with Lee Garmes, an influential American cinematographer of Hollywood’s classic era.
  • A. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • B. Peseux
    Peseux is a former municipality in the canton of Neuchâtel in western Switzerland, now part of the city of Neuchâtel.
  • C. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • D. Éveux
    Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
  • E. Cigales
    Cigales is a small town in the province of Valladolid, Spain, known historically as a royal residence and for its wine production.
  • 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_69c008db906c819096f3597d55d95432 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0686cc6d481909c62a29a84a4ce8e completed March 22, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65385f80081908e989b17529808c5 completed March 27, 2026, 9:53 a.m.
NEDg Description generation batch_69c6541014d88190a80baa7f5e94a7d8 completed March 27, 2026, 9:55 a.m.
NED2 Entity disambiguation (via description) batch_69c655140fbc8190ab8248a9e0c3de71 completed March 27, 2026, 9:59 a.m.
Created at: March 22, 2026, 4:34 p.m.