Triple

T15592364
Position Surface form Disambiguated ID Type / Status
Subject Henry Kolker E374776 entity
Predicate familyName P18 FINISHED
Object Kolker
Kolker is a surname most notably associated with American actor and film director Henry Kolker, active in the early 20th century.
 E1165388 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: Kolker | Statement: [Henry Kolker, familyName, Kolker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kolker
Context triple: [Henry Kolker, familyName, Kolker]
  • A. Kolnes
    Kolnes is a village in Karmøy municipality in Rogaland county, southwestern Norway, known for its residential character and proximity to the town of Haugesund.
  • B. Kolbu
    Kolbu is a village in Innlandet county, Norway, situated within the municipality of Østre Toten.
  • C. Kropinski
    Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
  • D. Kurnitz
    Kurnitz is a surname most notably associated with American playwright and screenwriter Harry Kurnitz.
  • E. Kierling
    Kierling is a small locality in Lower Austria best known as the place where writer Franz Kafka spent his final days and died.
  • 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: Kolker
Triple: [Henry Kolker, familyName, Kolker]
Generated description
Kolker is a surname most notably associated with American actor and film director Henry Kolker, active in the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kolker
Target entity description: Kolker is a surname most notably associated with American actor and film director Henry Kolker, active in the early 20th century.
  • A. Kolnes
    Kolnes is a village in Karmøy municipality in Rogaland county, southwestern Norway, known for its residential character and proximity to the town of Haugesund.
  • B. Kolbu
    Kolbu is a village in Innlandet county, Norway, situated within the municipality of Østre Toten.
  • C. Kropinski
    Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
  • D. Kurnitz
    Kurnitz is a surname most notably associated with American playwright and screenwriter Harry Kurnitz.
  • E. Kierling
    Kierling is a small locality in Lower Austria best known as the place where writer Franz Kafka spent his final days and died.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5e43d48190a8fd367f13f1c7e1 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c55fa248190b114a5b63560f87b completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff50020d748190be36f3c08df43e40 completed May 9, 2026, 3:17 p.m.
NED2 Entity disambiguation (via description) batch_69ff50a349688190ab7a18fa4460d86e completed May 9, 2026, 3:20 p.m.
Created at: April 10, 2026, 4:12 a.m.