Triple

T17680157
Position Surface form Disambiguated ID Type / Status
Subject Albion (2017) E440746 entity
Predicate featuresCharacter P626 FINISHED
Object Matthew
Matthew is a character in the 2017 film "Albion," a fantasy adventure story involving a young girl transported to a magical world.
E1282447 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: Matthew | Statement: [Albion (2017), featuresCharacter, Matthew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew
Context triple: [Albion (2017), featuresCharacter, Matthew]
  • A. John
    John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
  • B. John
    John is the given name of the late American comedian and actor John Belushi, famed for his work on "Saturday Night Live" and in films like "Animal House" and "The Blues Brothers."
  • C. John
    John is the given name of John A. Macdonald, the first prime minister of Canada and a key figure in the country's Confederation.
  • D. John
    John is the given name of John M. Grunsfeld, an American physicist, former NASA astronaut, and leader in space science and exploration.
  • E. John
    John II Casimir Vasa was a 17th-century King of Poland and Grand Duke of Lithuania from the Swedish House of Vasa.
  • 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: Matthew
Triple: [Albion (2017), featuresCharacter, Matthew]
Generated description
Matthew is a character in the 2017 film "Albion," a fantasy adventure story involving a young girl transported to a magical world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew
Target entity description: Matthew is a character in the 2017 film "Albion," a fantasy adventure story involving a young girl transported to a magical world.
  • A. Matthew
    Matthew is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s intricate romantic mystery.
  • B. Matthew
    Matthew is the given first name of American actor Ryan Phillippe, known for films like "Cruel Intentions" and "Crash."
  • C. Matthew
    Matthew is a person known primarily as Lisa's romantic partner.
  • D. Matthew
    Matthew is the given name of Matt Le Tissier, the renowned former Southampton and England footballer known for his exceptional skill and loyalty to a single club.
  • E. Matthew
    Matthew is the first name of American film director and producer Jay Roach, known for comedies like the Austin Powers and Meet the Parents series.
  • 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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4704357b8819087e3a93e9eefd858 completed April 19, 2026, 6:03 a.m.
NED1 Entity disambiguation (via context triple) batch_6a022327dbf8819083cc9366ddcf3ed2 completed May 11, 2026, 6:42 p.m.
NEDg Description generation batch_6a02245658108190ab50ffb98eef589b completed May 11, 2026, 6:47 p.m.
NED2 Entity disambiguation (via description) batch_6a0224c554788190ae1aa7d4e7211aaf completed May 11, 2026, 6:49 p.m.
Created at: April 10, 2026, 10:01 a.m.