Triple

T15160123
Position Surface form Disambiguated ID Type / Status
Subject Andrea Leeds E362187 entity
Predicate familyName P18 FINISHED
Object Lees
Lees is the surname of Andrea Leeds, an American film actress prominent in the 1930s and 1940s.
E1140776 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: Lees | Statement: [Andrea Leeds, familyName, Lees]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lees
Context triple: [Andrea Leeds, familyName, Lees]
  • A. Lees
    Lees is a village in the Metropolitan Borough of Oldham, Greater Manchester, England, historically part of Lancashire.
  • B. Léez
    Léez is a river in southwestern France that serves as a tributary within the Gave de Pau river system.
  • C. Leer
    Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
  • D. Lleó
    Lleó is a Spanish-language surname of Catalan origin borne by various individuals, including Cuban jurist and former president Manuel Urrutia Lleó.
  • E. Leens
    Leens is a village in the Dutch province of Groningen, located within the municipality of Het Hogeland.
  • 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: Lees
Triple: [Andrea Leeds, familyName, Lees]
Generated description
Lees is the surname of Andrea Leeds, an American film actress prominent in the 1930s and 1940s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lees
Target entity description: Lees is the surname of Andrea Leeds, an American film actress prominent in the 1930s and 1940s.
  • A. Lees
    Lees is a village in the Metropolitan Borough of Oldham, Greater Manchester, England, historically part of Lancashire.
  • B. Léez
    Léez is a river in southwestern France that serves as a tributary within the Gave de Pau river system.
  • C. Leer
    Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
  • D. Lleó
    Lleó is a Spanish-language surname of Catalan origin borne by various individuals, including Cuban jurist and former president Manuel Urrutia Lleó.
  • E. Leens
    Leens is a village in the Dutch province of Groningen, located within the municipality of Het Hogeland.
  • 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_69d85a087b7c81908baa94a53dac8d68 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0060dd71881908ecc4a4f52d438a5 completed April 15, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69febffaa4b88190aab36fdae057e6d2 completed May 9, 2026, 5:02 a.m.
NEDg Description generation batch_69fec23c83ac819087633c0f64e50506 completed May 9, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69fec2f95a408190850e4d81839822ba completed May 9, 2026, 5:15 a.m.
Created at: April 10, 2026, 3:08 a.m.