Triple

T7143273
Position Surface form Disambiguated ID Type / Status
Subject Rita Tushingham E166501 entity
Predicate notableWork P4 FINISHED
Object Girl with Green Eyes
Girl with Green Eyes is a 1964 British drama film, adapted from Edna O’Brien’s novel, about a shy Irish country girl’s complicated romance in Dublin.
E644826 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: Girl with Green Eyes | Statement: [Rita Tushingham, notableWork, Girl with Green Eyes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Girl with Green Eyes
Context triple: [Rita Tushingham, notableWork, Girl with Green Eyes]
  • A. Green Eyes
    "Green Eyes" is a soulful, jazz-inflected R&B song by Erykah Badu from her acclaimed album *Mama’s Gun*, noted for its emotional vulnerability and evolving three-part structure.
  • B. Your Girl
    "Your Girl" is a song by Mariah Carey from her 2005 album *The Emancipation of Mimi*.
  • C. Of the Girl
    "Of the Girl" is a moody, atmospheric rock song by Pearl Jam from their 2000 album "Binaural."
  • D. The Girl Was Young
    The Girl Was Young is a song by British rock musician Ian Hunter, known for its reflective lyrics and melodic rock style.
  • E. Looking for the Girl
    "Looking for the Girl" is a short story by Neil Gaiman, featured in his collection *Smoke and Mirrors*, that blends dark fantasy with themes of obsession and memory.
  • 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: Girl with Green Eyes
Triple: [Rita Tushingham, notableWork, Girl with Green Eyes]
Generated description
Girl with Green Eyes is a 1964 British drama film, adapted from Edna O’Brien’s novel, about a shy Irish country girl’s complicated romance in Dublin.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Girl with Green Eyes
Target entity description: Girl with Green Eyes is a 1964 British drama film, adapted from Edna O’Brien’s novel, about a shy Irish country girl’s complicated romance in Dublin.
  • A. Green Eyes
    "Green Eyes" is a soulful, jazz-inflected R&B song by Erykah Badu from her acclaimed album *Mama’s Gun*, noted for its emotional vulnerability and evolving three-part structure.
  • B. Your Girl
    "Your Girl" is a song by Mariah Carey from her 2005 album *The Emancipation of Mimi*.
  • C. Of the Girl
    "Of the Girl" is a moody, atmospheric rock song by Pearl Jam from their 2000 album "Binaural."
  • D. The Girl Was Young
    The Girl Was Young is a song by British rock musician Ian Hunter, known for its reflective lyrics and melodic rock style.
  • E. Looking for the Girl
    "Looking for the Girl" is a short story by Neil Gaiman, featured in his collection *Smoke and Mirrors*, that blends dark fantasy with themes of obsession and memory.
  • 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_69c6888579d481909e05a8d6b81bf733 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e7d027d0819088598b2a9f71b1b7 completed March 27, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad98576481908b8b82f675079fca completed March 28, 2026, 10:29 a.m.
NEDg Description generation batch_69c7ae1bde448190b546d292d213c8c9 completed March 28, 2026, 10:31 a.m.
NED2 Entity disambiguation (via description) batch_69c7ae73e1a88190a18488b3155b2542 completed March 28, 2026, 10:33 a.m.
Created at: March 27, 2026, 2:46 p.m.