Triple

T6638133
Position Surface form Disambiguated ID Type / Status
Subject Steve Bloomer E150509 entity
Predicate familyName P18 FINISHED
Object Bloomer
Bloomer is an English surname most famously associated with Steve Bloomer, a prolific early 20th-century footballer and record goal-scorer.
 E607007 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: Bloomer | Statement: [Steve Bloomer, familyName, Bloomer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bloomer
Context triple: [Steve Bloomer, familyName, Bloomer]
  • A. Bloomer Girl
    Bloomer Girl is a 1944 Broadway musical that blends romance and social commentary, notable for its progressive themes about women's rights and abolitionism.
  • B. Fawcett
    Fawcett is a surname most famously associated with British explorer Percy Fawcett, known for his expeditions in the Amazon and his mysterious disappearance while searching for the lost city of "Z."
  • C. Bettie
    Bettie is a feminine given name, often used as a diminutive or variant of names like Bettina or Elizabeth.
  • D. Betsy
    Betsy is a common diminutive or nickname for the given name Elizabeth.
  • E. Betsy
    Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
  • 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: Bloomer
Triple: [Steve Bloomer, familyName, Bloomer]
Generated description
Bloomer is an English surname most famously associated with Steve Bloomer, a prolific early 20th-century footballer and record goal-scorer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bloomer
Target entity description: Bloomer is an English surname most famously associated with Steve Bloomer, a prolific early 20th-century footballer and record goal-scorer.
  • A. Bloomer Girl
    Bloomer Girl is a 1944 Broadway musical that blends romance and social commentary, notable for its progressive themes about women's rights and abolitionism.
  • B. Fawcett
    Fawcett is a surname most famously associated with British explorer Percy Fawcett, known for his expeditions in the Amazon and his mysterious disappearance while searching for the lost city of "Z."
  • C. Bettie
    Bettie is a feminine given name, often used as a diminutive or variant of names like Bettina or Elizabeth.
  • D. Betsy
    Betsy is a common diminutive or nickname for the given name Elizabeth.
  • E. Betsy
    Betsy is a key female character in the 1976 film "Taxi Driver," known as the idealistic campaign worker who becomes the object of Travis Bickle’s fixation.
  • 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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff082b0819089f5a69aa67d5346 completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e453cb14819093597dda825b4304 completed March 27, 2026, 8:10 p.m.
NEDg Description generation batch_69c6e5b353c88190817b62290eefc382 completed March 27, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_69c6e669830c8190bc881cb106125ec8 completed March 27, 2026, 8:19 p.m.
Created at: March 27, 2026, 2 p.m.