Triple

T15367522
Position Surface form Disambiguated ID Type / Status
Subject Solo: A Star Wars Story (film score) E367455 entity
Predicate hasPart P35 FINISHED
Object Meet Han
"Meet Han" is a musical cue from the Solo: A Star Wars Story film score that underscores the introduction and early characterization of Han Solo.
E1153101 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: Meet Han | Statement: [Solo: A Star Wars Story (film score), hasPart, Meet Han]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meet Han
Context triple: [Solo: A Star Wars Story (film score), hasPart, Meet Han]
  • A. Hasa Diga Eebowai
    "Hasa Diga Eebowai" is a satirical, profanity-laced ensemble song from the Broadway musical *The Book of Mormon* that expresses villagers’ frustration with God through dark humor.
  • B. Meeting Neil
    "Meeting Neil" is a track from Ludwig Göransson's score for Christopher Nolan's science-fiction thriller film *Tenet*.
  • C. Hanacaraka
    Hanacaraka is the traditional Javanese writing system used historically on the island of Java for literary, religious, and everyday texts.
  • D. Ecco
    Ecco is a time-traveling bottlenose dolphin and the protagonist of the classic Sega action-adventure video game series "Ecco the Dolphin."
  • E. Ecco
    Ecco is a literary imprint known for publishing high-quality fiction, nonfiction, and poetry under the HarperCollins umbrella.
  • 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: Meet Han
Triple: [Solo: A Star Wars Story (film score), hasPart, Meet Han]
Generated description
"Meet Han" is a musical cue from the Solo: A Star Wars Story film score that underscores the introduction and early characterization of Han Solo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Meet Han
Target entity description: "Meet Han" is a musical cue from the Solo: A Star Wars Story film score that underscores the introduction and early characterization of Han Solo.
  • A. Hasa Diga Eebowai
    "Hasa Diga Eebowai" is a satirical, profanity-laced ensemble song from the Broadway musical *The Book of Mormon* that expresses villagers’ frustration with God through dark humor.
  • B. Meeting Neil
    "Meeting Neil" is a track from Ludwig Göransson's score for Christopher Nolan's science-fiction thriller film *Tenet*.
  • C. Hanacaraka
    Hanacaraka is the traditional Javanese writing system used historically on the island of Java for literary, religious, and everyday texts.
  • D. Ecco
    Ecco is a time-traveling bottlenose dolphin and the protagonist of the classic Sega action-adventure video game series "Ecco the Dolphin."
  • E. Ecco
    Ecco is a literary imprint known for publishing high-quality fiction, nonfiction, and poetry under the HarperCollins umbrella.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e4a7cdc8190b7b48c97e774c306 completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b4e968c8190a16824ee3ede13b2 completed May 9, 2026, 10:24 a.m.
NEDg Description generation batch_69ff0dc93af88190ae34fa3983aac820 completed May 9, 2026, 10:34 a.m.
NED2 Entity disambiguation (via description) batch_69ff0e467a148190871cb8a2dc660e06 completed May 9, 2026, 10:36 a.m.
Created at: April 10, 2026, 3:18 a.m.