Triple

T16438974
Position Surface form Disambiguated ID Type / Status
Subject Take Back the City E399247 entity
Predicate writer P1360 FINISHED
Object Nathan Connolly
Nathan Connolly is a writer best known for his work on the political drama film "Take Back the City."
E1230521 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: Nathan Connolly | Statement: [Take Back the City, writer, Nathan Connolly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathan Connolly
Context triple: [Take Back the City, writer, Nathan Connolly]
  • A. Nathan Connolly
    Nathan Connolly is a contemporary writer best known for his work on the novel "Signal Fire."
  • B. Nathan Connolly
    Nathan Connolly is a Northern Irish musician best known as the lead guitarist and backing vocalist of the alternative rock band Snow Patrol.
  • C. Ryan Connolly
    Ryan Connolly is a filmmaker and YouTube personality best known for creating the popular filmmaking education channel Film Riot.
  • D. Chris Connolly
    Chris Connolly is a personal name shared by multiple individuals, including professionals in fields such as sports, media, and the arts.
  • E. Luke Doolan
    Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
  • 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: Nathan Connolly
Triple: [Take Back the City, writer, Nathan Connolly]
Generated description
Nathan Connolly is a writer best known for his work on the political drama film "Take Back the City."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nathan Connolly
Target entity description: Nathan Connolly is a writer best known for his work on the political drama film "Take Back the City."
  • A. Nathan Connolly
    Nathan Connolly is a Northern Irish musician best known as the lead guitarist and backing vocalist of the alternative rock band Snow Patrol.
  • B. Nathan Connolly
    Nathan Connolly is a contemporary writer best known for his work on the novel "Signal Fire."
  • C. Ryan Connolly
    Ryan Connolly is a filmmaker and YouTube personality best known for creating the popular filmmaking education channel Film Riot.
  • D. Chris Connolly
    Chris Connolly is a personal name shared by multiple individuals, including professionals in fields such as sports, media, and the arts.
  • E. Luke Doolan
    Luke Doolan is an Australian film editor and filmmaker best known for his work on acclaimed films such as "Animal Kingdom."
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba720a48190b0b412225e993e52 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a009d27712081908530bbf0d9d47e1f completed May 10, 2026, 2:58 p.m.
NEDg Description generation batch_6a009e1aa6548190b77def9f74d3272a completed May 10, 2026, 3:02 p.m.
NED2 Entity disambiguation (via description) batch_6a009eb06d6481909914286301f9b4db completed May 10, 2026, 3:05 p.m.
Created at: April 10, 2026, 5:10 a.m.