Triple

T15798813
Position Surface form Disambiguated ID Type / Status
Subject The Blow E383045 entity
Predicate associatedAct P37 FINISHED
Object Dear Nora
Dear Nora is an indie pop/folk project known for its intimate, lo-fi songs and reflective, narrative-driven lyrics.
E1177181 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: Dear Nora | Statement: [The Blow, associatedAct, Dear Nora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dear Nora
Context triple: [The Blow, associatedAct, Dear Nora]
  • A. Dear Maria
    "Dear Maria" is a track from the hip-hop album "You Only Live 2wice" by American rapper Freddie Gibbs.
  • B. Dear Frankie
    Dear Frankie is a 2004 Scottish drama film about a single mother who fabricates letters from her young son's absent father, starring Emily Mortimer and Gerard Butler.
  • C. Dear Marie
    "Dear Marie" is a song by John Mayer from his 2012 album "Paradise Valley," reflecting on a youthful romance and the passage of time.
  • D. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • E. Dear John
    Dear John is an American sitcom that aired from 1988 to 1992, starring Judd Hirsch as a recently divorced man navigating single life and friendships in a New York City support group.
  • 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: Dear Nora
Triple: [The Blow, associatedAct, Dear Nora]
Generated description
Dear Nora is an indie pop/folk project known for its intimate, lo-fi songs and reflective, narrative-driven lyrics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dear Nora
Target entity description: Dear Nora is an indie pop/folk project known for its intimate, lo-fi songs and reflective, narrative-driven lyrics.
  • A. Dear Maria
    "Dear Maria" is a track from the hip-hop album "You Only Live 2wice" by American rapper Freddie Gibbs.
  • B. Dear Frankie
    Dear Frankie is a 2004 Scottish drama film about a single mother who fabricates letters from her young son's absent father, starring Emily Mortimer and Gerard Butler.
  • C. Dear Marie
    "Dear Marie" is a song by John Mayer from his 2012 album "Paradise Valley," reflecting on a youthful romance and the passage of time.
  • D. Dear John
    Dear John is a romantic drama film based on Nicholas Sparks' novel, following the relationship between a soldier and a young woman whose love is tested by distance and time.
  • E. Dear John
    "Dear John" is a six-minute country-pop ballad by Taylor Swift widely noted for its confessional lyrics about a toxic relationship and emotional manipulation.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b4e00d348190bc98917c4098ec2f completed April 16, 2026, 10:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90b08ab48190892c700f5eb261d8 completed May 9, 2026, 7:53 p.m.
NEDg Description generation batch_69ff936cbbc8819097958ac02673a474 completed May 9, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_69ff93ed15ec8190b9361f7ad4c7e447 completed May 9, 2026, 8:07 p.m.
Created at: April 10, 2026, 4:48 a.m.