Triple

T13014551
Position Surface form Disambiguated ID Type / Status
Subject Liza Marshall E322513 entity
Predicate notableWork P4 FINISHED
Object Temple
"Temple" is a British television drama series produced by Liza Marshall, centered on an underground clinic beneath London where a surgeon treats criminals and desperate patients.
 E1015940 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: Temple | Statement: [Liza Marshall, notableWork, Temple]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Temple
Context triple: [Liza Marshall, notableWork, Temple]
  • A. Temple
    Temple is a mid-sized city in central Texas known as a regional medical and transportation hub.
  • B. Temple
    Temple is a surname of English origin borne by various notable individuals across fields such as politics, sports, and the arts.
  • C. Temple
    Temple is a Paris Métro station in central Paris, serving line 3 near the Place de la République.
  • D. Temple
    Temple is a historic legal district in central London, renowned for housing the Inns of Court and many barristers’ chambers.
  • E. Temple
    Temple is the athletic program of Temple University, best known for its NCAA Division I sports teams, particularly in basketball and football.
  • 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: Temple
Triple: [Liza Marshall, notableWork, Temple]
Generated description
"Temple" is a British television drama series produced by Liza Marshall, centered on an underground clinic beneath London where a surgeon treats criminals and desperate patients.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Temple
Target entity description: "Temple" is a British television drama series produced by Liza Marshall, centered on an underground clinic beneath London where a surgeon treats criminals and desperate patients.
  • A. Temple
    Temple is a historic legal district in central London, renowned for housing the Inns of Court and many barristers’ chambers.
  • B. Temple
    Temple is a surname of English origin borne by various notable individuals across fields such as politics, sports, and the arts.
  • C. Temple
    Temple is a mid-sized city in central Texas known as a regional medical and transportation hub.
  • D. Temple
    Temple is a Paris Métro station in central Paris, serving line 3 near the Place de la République.
  • E. Temple
    Temple is the athletic program of Temple University, best known for its NCAA Division I sports teams, particularly in basketball and football.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecd04748190ade2530ee5db35fe completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c11290e08190a41c162d47094203 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c20a1eb881908a28dc884c2005ef completed May 3, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69f6c34b9ec08190bb29458b6f43c388 completed May 3, 2026, 3:38 a.m.
Created at: April 9, 2026, 8:50 p.m.