Triple

T11899718
Position Surface form Disambiguated ID Type / Status
Subject Sick Boy E283117 entity
Predicate writer P1360 FINISHED
Object Tony Ann
Tony Ann is a contemporary pianist and composer known for his emotive, cinematic piano pieces and strong online following.
E953606 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: Tony Ann | Statement: [Sick Boy, writer, Tony Ann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tony Ann
Context triple: [Sick Boy, writer, Tony Ann]
  • A. Toni May
    Toni May is a personal name, most likely referring to an individual whose specific public identity or achievements are not widely documented.
  • B. Annie Montrose
    Annie Montrose is the sharp-tongued, media-savvy NASA Director of Media Relations in Andy Weir’s science fiction novel (and its film adaptation) "The Martian."
  • C. Sheri Annis
    Sheri Annis is a Republican political consultant and media strategist known for her work on ballot initiatives and as a conservative commentator.
  • D. Toni Stevens
    Toni Stevens is a film producer known for her work on the animated feature "PAW Patrol: The Movie."
  • E. Toni Lawrence
    Toni Lawrence is an American actress known for her film and television work in the 1970s and 1980s.
  • 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: Tony Ann
Triple: [Sick Boy, writer, Tony Ann]
Generated description
Tony Ann is a contemporary pianist and composer known for his emotive, cinematic piano pieces and strong online following.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tony Ann
Target entity description: Tony Ann is a contemporary pianist and composer known for his emotive, cinematic piano pieces and strong online following.
  • A. Toni May
    Toni May is a personal name, most likely referring to an individual whose specific public identity or achievements are not widely documented.
  • B. Annie Montrose
    Annie Montrose is the sharp-tongued, media-savvy NASA Director of Media Relations in Andy Weir’s science fiction novel (and its film adaptation) "The Martian."
  • C. Sheri Annis
    Sheri Annis is a Republican political consultant and media strategist known for her work on ballot initiatives and as a conservative commentator.
  • D. Toni Stevens
    Toni Stevens is a film producer known for her work on the animated feature "PAW Patrol: The Movie."
  • E. Toni Lawrence
    Toni Lawrence is an American actress known for her film and television work in the 1970s and 1980s.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd16433881909befca9774bdaab4 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4182f18c08190b22706b024d60dd7 completed May 1, 2026, 3:04 a.m.
NEDg Description generation batch_69f41f1c21388190b6ecb0fd602abb7d completed May 1, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f4228a73708190a6d2db321e175921 completed May 1, 2026, 3:48 a.m.
Created at: April 8, 2026, 9:44 p.m.