Triple

T8965872
Position Surface form Disambiguated ID Type / Status
Subject Margaret Pomeranz E214130 entity
Predicate familyName P18 FINISHED
Object Pomeranz
Pomeranz is a surname most notably associated with Australian film critic and television personality Margaret Pomeranz.
E768856 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: Pomeranz | Statement: [Margaret Pomeranz, familyName, Pomeranz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pomeranz
Context triple: [Margaret Pomeranz, familyName, Pomeranz]
  • A. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • B. Pomarance
    Pomarance is a historic Tuscan town in central Italy, known for its medieval architecture and proximity to the geothermal area of Larderello.
  • C. Pohlmann
    Pohlmann was a European officer who became a senior commander in the Maratha army and led its forces against the British at the Battle of Assaye in 1803.
  • D. Paepcke
    Paepcke is a surname most notably associated with Walter Paepcke, the American industrialist and cultural philanthropist who founded the Aspen Institute.
  • E. Dombrowski
    Dombrowski is a surname most prominently associated with Dave Dombrowski, a longtime Major League Baseball executive known for leading multiple franchises to pennants and World Series titles.
  • 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: Pomeranz
Triple: [Margaret Pomeranz, familyName, Pomeranz]
Generated description
Pomeranz is a surname most notably associated with Australian film critic and television personality Margaret Pomeranz.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pomeranz
Target entity description: Pomeranz is a surname most notably associated with Australian film critic and television personality Margaret Pomeranz.
  • A. Blaustein
    Blaustein is a municipality in the Alb-Donau district of Baden-Württemberg in southern Germany, situated near the city of Ulm.
  • B. Pomarance
    Pomarance is a historic Tuscan town in central Italy, known for its medieval architecture and proximity to the geothermal area of Larderello.
  • C. Pohlmann
    Pohlmann was a European officer who became a senior commander in the Maratha army and led its forces against the British at the Battle of Assaye in 1803.
  • D. Paepcke
    Paepcke is a surname most notably associated with Walter Paepcke, the American industrialist and cultural philanthropist who founded the Aspen Institute.
  • E. Dombrowski
    Dombrowski is a surname most prominently associated with Dave Dombrowski, a longtime Major League Baseball executive known for leading multiple franchises to pennants and World Series titles.
  • 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_69ca839cd6008190a1546a701a56710c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc67623818819096aee155a9b43e8f completed April 1, 2026, 12:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc95514408190ad442069daec0459 completed April 3, 2026, 2:06 p.m.
NEDg Description generation batch_69cfc9e01dc88190aeedcd9fb3281688 completed April 3, 2026, 2:08 p.m.
NED2 Entity disambiguation (via description) batch_69cfca4374c481909ceefcfb1a31bed2 completed April 3, 2026, 2:10 p.m.
Created at: March 30, 2026, 7:01 p.m.