Triple

T19095519
Position Surface form Disambiguated ID Type / Status
Subject Blue Bayou E467393 entity
Predicate cinematography P1953 FINISHED
Object Matthew Chuang
Matthew Chuang is a cinematographer known for his visually distinctive work on the film "Blue Bayou."
E1359397 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 Chuang | Statement: [Blue Bayou, cinematography, Matthew Chuang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Chuang
Context triple: [Blue Bayou, cinematography, Matthew Chuang]
  • A. Michael Wong
    Michael Wong is a Hong Kong-based actor and singer known for his roles in action and crime films across Asian cinema.
  • B. Lawrence Chu
    Lawrence Chu is a Chinese-American chef and restaurateur best known as the father of film director Jon M. Chu.
  • C. Curtis Chin
    Curtis Chin is an Asian American writer, filmmaker, and activist known for co-founding the Asian American Writers’ Workshop and for his work highlighting Asian American experiences and social justice issues.
  • D. Andrew Hsia
    Andrew Hsia is a Taiwanese politician and diplomat known for serving in senior cross-strait and foreign affairs roles, including leadership positions in Taiwan’s Mainland policy and its foreign ministry.
  • E. Jeffrey Wu
    Jeffrey Wu is a researcher in artificial intelligence and machine learning, known for his contributions to large language models and few-shot learning.
  • 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 Chuang
Triple: [Blue Bayou, cinematography, Matthew Chuang]
Generated description
Matthew Chuang is a cinematographer known for his visually distinctive work on the film "Blue Bayou."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew Chuang
Target entity description: Matthew Chuang is a cinematographer known for his visually distinctive work on the film "Blue Bayou."
  • A. Michael Wong
    Michael Wong is a Hong Kong-based actor and singer known for his roles in action and crime films across Asian cinema.
  • B. Lawrence Chu
    Lawrence Chu is a Chinese-American chef and restaurateur best known as the father of film director Jon M. Chu.
  • C. Curtis Chin
    Curtis Chin is an Asian American writer, filmmaker, and activist known for co-founding the Asian American Writers’ Workshop and for his work highlighting Asian American experiences and social justice issues.
  • D. Andrew Hsia
    Andrew Hsia is a Taiwanese politician and diplomat known for serving in senior cross-strait and foreign affairs roles, including leadership positions in Taiwan’s Mainland policy and its foreign ministry.
  • E. Jeffrey Wu
    Jeffrey Wu is a researcher in artificial intelligence and machine learning, known for his contributions to large language models and few-shot learning.
  • 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_69d8dd05ac4c8190b1967d8f97f3fb2f completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e368f20c8190bd84d2ba320991ac completed April 20, 2026, 8:27 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05e669d35c819099e2152231197c27 completed May 14, 2026, 3:12 p.m.
NEDg Description generation batch_6a05e87086048190bb33e123a75d6b56 completed May 14, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_6a05e8f73de48190831b72700709055e completed May 14, 2026, 3:23 p.m.
Created at: April 10, 2026, 12:04 p.m.