Triple

T2804035
Position Surface form Disambiguated ID Type / Status
Subject Wicker Park E54009 entity
Predicate mainCharacter P1183 FINISHED
Object 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.
 E299549 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: [Wicker Park, mainCharacter, Matthew]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Matthew
Context triple: [Wicker Park, mainCharacter, Matthew]
  • A. Matthew
    Matthew is the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
  • B. Matthew
    Matthew is traditionally recognized as one of the Twelve Apostles of Jesus and is commonly associated with the authorship of the Gospel of Matthew in the New Testament.
  • C. James
    James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
  • D. James
    James is a prominent early Christian figure, traditionally identified as James the brother of Jesus and a leader in the Jerusalem church.
  • E. Patrick
    Patrick is a component or constituent part of something associated with or named Kirkpatrick.
  • 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: [Wicker Park, mainCharacter, Matthew]
Generated description
Matthew is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s intricate romantic mystery.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Matthew
Target entity description: Matthew is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s intricate romantic mystery.
  • A. Matthew
    Matthew is the given name of Sir Matt Busby, the legendary Scottish football manager best known for his long and successful tenure at Manchester United.
  • B. Matthew
    Matthew is traditionally recognized as one of the Twelve Apostles of Jesus and is commonly associated with the authorship of the Gospel of Matthew in the New Testament.
  • C. James
    James is a common masculine given name of Hebrew origin meaning "supplanter," widely used in English-speaking countries.
  • D. James
    James is a prominent early Christian figure, traditionally identified as James the brother of Jesus and a leader in the Jerusalem church.
  • E. Patrick
    Patrick is the given first name of Pat Riley, the famed American basketball coach and executive.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde1409148190a06a401185a26b64 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc674217c81908177b088cc824e7b completed March 10, 2026, 7:21 a.m.
NEDg Description generation batch_69afc863133c8190b129a55f8d28966f completed March 10, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_69afc8d43e608190b33159a464dc2e8c completed March 10, 2026, 7:31 a.m.
Created at: March 6, 2026, 9:59 p.m.