Triple

T31208616
Position Surface form Disambiguated ID Type / Status
Subject The F Word E795672 entity
Predicate mpaaTitleInUS P171031 FINISHED
Object What If
What If is a 2013 romantic comedy film starring Daniel Radcliffe and Zoe Kazan, centered on two friends navigating the possibility of turning their close friendship into a romantic relationship.
 E795673 NE FINISHED

How this triple was built (3 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: What If | Statement: [The F Word, mpaaTitleInUS, What If]
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: What If
Triple: [The F Word, mpaaTitleInUS, What If]
Generated description
What If is a 2013 romantic comedy film starring Daniel Radcliffe and Zoe Kazan, centered on two friends navigating the possibility of turning their close friendship into a romantic relationship.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: mpaaTitleInUS
Context triple: [The F Word, mpaaTitleInUS, What If]
  • A. mpaaRating
    Indicates the official Motion Picture Association of America (MPAA) content rating assigned to a film or audiovisual work.
  • B. TVRatingUS
    Indicates the television content rating assigned to a program under the U.S. TV parental guidelines system.
  • C. USRating
    Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or system.
  • D. televisionRatingUS
    Indicates the official content rating assigned to a television program under the United States TV rating system.
  • E. mpaaEra
    Indicates the MPAA rating era or classification period under which a work was evaluated or released.
  • F. None of above. chosen

Provenance (7 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_69f224d8c6608190b7882466521f62be completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69c25dff481908c9ecd0bfa358a6f completed May 3, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296bda08488190aa10841f9acb6aa2 completed June 10, 2026, 1:51 p.m.
NEDg Description generation batch_6a2973423590819097df33760a2d14ca completed June 10, 2026, 2:22 p.m.
NED2 Entity disambiguation (via description) batch_6a299c9b54dc8190abd715cd88979541 completed June 10, 2026, 5:19 p.m.
PD Predicate disambiguation batch_69f696673214819094350e1d2648ef34 completed May 3, 2026, 12:27 a.m.
PDg Predicate description generation batch_69f6978ec27c8190a488e1f9c2566d38 completed May 3, 2026, 12:32 a.m.
Created at: April 29, 2026, 9:09 p.m.