Triple

T6589304
Position Surface form Disambiguated ID Type / Status
Subject Joe E159307 entity
Predicate notableWork P4 FINISHED
Object The Love Scene
The Love Scene is a creative work—likely a film, play, or literary piece—best known as one of Joe’s most recognized and discussed projects.
 E603378 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: The Love Scene | Statement: [Joe, notableWork, The Love Scene]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Love Scene
Context triple: [Joe, notableWork, The Love Scene]
  • A. The Tavern Scene
    The Tavern Scene is a genre painting by Dutch Golden Age artist Abraham Bloemaert depicting lively social life in a rustic inn.
  • B. Chapel of Love
    "Chapel of Love" is a classic pop song, originally made famous by The Dixie Cups in 1964, that has been covered by numerous artists including Bette Midler.
  • C. Lovers
    Lovers is a Spanish film featuring actress Maribel Verdú in one of her notable roles.
  • D. Two Lovers
    Two Lovers is a 2008 romantic drama film directed by James Gray that follows a troubled man torn between a stable relationship and a passionate but complicated affair.
  • E. The Serenade
    The Serenade is a romantic comic opera by composer Victor Herbert that helped establish his reputation in early American musical theater.
  • 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: The Love Scene
Triple: [Joe, notableWork, The Love Scene]
Generated description
The Love Scene is a creative work—likely a film, play, or literary piece—best known as one of Joe’s most recognized and discussed projects.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: The Love Scene
Target entity description: The Love Scene is a creative work—likely a film, play, or literary piece—best known as one of Joe’s most recognized and discussed projects.
  • A. The Tavern Scene
    The Tavern Scene is a genre painting by Dutch Golden Age artist Abraham Bloemaert depicting lively social life in a rustic inn.
  • B. Chapel of Love
    "Chapel of Love" is a classic pop song, originally made famous by The Dixie Cups in 1964, that has been covered by numerous artists including Bette Midler.
  • C. Lovers
    Lovers is a Spanish film featuring actress Maribel Verdú in one of her notable roles.
  • D. Two Lovers
    Two Lovers is a 2008 romantic drama film directed by James Gray that follows a troubled man torn between a stable relationship and a passionate but complicated affair.
  • E. The Serenade
    The Serenade is a romantic comic opera by composer Victor Herbert that helped establish his reputation in early American musical theater.
  • 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_69c688366ce8819083f8883983c0df92 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6aeb201e88190808cf5779349f96c completed March 27, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d57bde388190919ff6820e1b9610 completed March 27, 2026, 7:07 p.m.
NEDg Description generation batch_69c6d6adc8c88190aa4ed066a2c99657 completed March 27, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69c6d8486534819080b75cad9cc32276 completed March 27, 2026, 7:19 p.m.
Created at: March 27, 2026, 1:55 p.m.