Triple

T1638065
Position Surface form Disambiguated ID Type / Status
Subject Millar E35402 entity
Predicate relatedSurname P13741 FINISHED
Object Millner
Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
E183622 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: Millner | Statement: [Millar, relatedSurname, Millner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Millner
Context triple: [Millar, relatedSurname, Millner]
  • A. Menzel
    Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
  • B. Miller
    Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
  • C. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • D. Müller
    Müller is a common German surname, equivalent to "Miller" in English, historically associated with the occupation of operating a mill.
  • E. Moynier
    Moynier is a Swiss surname most notably associated with Gustave Moynier, a co-founder and long-serving president of the International Committee of the Red Cross.
  • 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: Millner
Triple: [Millar, relatedSurname, Millner]
Generated description
Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Millner
Target entity description: Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
  • A. Menzel
    Menzel is the surname of Idina Menzel, the American actress and singer best known for her roles in Broadway musicals and the film "Frozen."
  • B. Miller
    Miller is a common English and Scottish occupational surname historically given to people who worked in grain mills.
  • C. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • D. Müller
    Müller is a common German surname, equivalent to "Miller" in English, historically associated with the occupation of operating a mill.
  • E. Moynier
    Moynier is a Swiss surname most notably associated with Gustave Moynier, a co-founder and long-serving president of the International Committee of the Red Cross.
  • 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_69a88604618c81908b41f6429c431eb6 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61e142ac8190aa2fbd8f0826b5b2 completed March 6, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad58ddfdbc819096578412818fdfbf completed March 8, 2026, 11:09 a.m.
NEDg Description generation batch_69ad595841788190a97bbfded30110c5 completed March 8, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_69ad59f329cc8190814de211fb00c7b8 completed March 8, 2026, 11:13 a.m.
Created at: March 4, 2026, 7:28 p.m.