Triple

T12767962
Position Surface form Disambiguated ID Type / Status
Subject The Dish E305172 entity
Predicate cinematographyBy P1953 FINISHED
Object Graeme Wood
Graeme Wood is a cinematographer best known for his work on the Australian film "The Dish."
E1002555 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: Graeme Wood | Statement: [The Dish, cinematographyBy, Graeme Wood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Graeme Wood
Context triple: [The Dish, cinematographyBy, Graeme Wood]
  • A. Graeme Wood
    Graeme Wood is an Australian entrepreneur best known as the founder of the online travel booking company Wotif.com.
  • B. Tom Reese
    Tom Reese was an American character actor known for his tough-guy roles in numerous Westerns and television series from the 1950s through the 1980s.
  • C. Bret Stephens
    Bret Stephens is an American conservative journalist and columnist known for his incisive political commentary and foreign policy analysis.
  • D. Gareth Porter
    Gareth Porter is an American investigative journalist and historian known for his critical reporting on U.S. foreign policy and national security issues.
  • E. Michael Tomasky
    Michael Tomasky is an American journalist, author, and political commentator known for his liberal analysis and leadership roles at prominent opinion magazines.
  • 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: Graeme Wood
Triple: [The Dish, cinematographyBy, Graeme Wood]
Generated description
Graeme Wood is a cinematographer best known for his work on the Australian film "The Dish."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Graeme Wood
Target entity description: Graeme Wood is a cinematographer best known for his work on the Australian film "The Dish."
  • A. Graeme Wood
    Graeme Wood is an Australian entrepreneur best known as the founder of the online travel booking company Wotif.com.
  • B. Tom Reese
    Tom Reese was an American character actor known for his tough-guy roles in numerous Westerns and television series from the 1950s through the 1980s.
  • C. Bret Stephens
    Bret Stephens is an American conservative journalist and columnist known for his incisive political commentary and foreign policy analysis.
  • D. Gareth Porter
    Gareth Porter is an American investigative journalist and historian known for his critical reporting on U.S. foreign policy and national security issues.
  • E. Michael Tomasky
    Michael Tomasky is an American journalist, author, and political commentator known for his liberal analysis and leadership roles at prominent opinion magazines.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df3b2f88190b37b696400178795 completed April 10, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684f750a08190abf6122baa579bc4 completed May 2, 2026, 11:12 p.m.
NEDg Description generation batch_69f6890782c48190ae93866cf39b1c25 completed May 2, 2026, 11:30 p.m.
NED2 Entity disambiguation (via description) batch_69f68976b60881908abf5b69b8c37e6e completed May 2, 2026, 11:32 p.m.
Created at: April 9, 2026, 5:28 p.m.