Triple

T9649096
Position Surface form Disambiguated ID Type / Status
Subject Paul Fix E233287 entity
Predicate familyName P18 FINISHED
Object Fix
Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
 E811792 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: Fix | Statement: [Paul Fix, familyName, Fix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fix
Context triple: [Paul Fix, familyName, Fix]
  • A. Fixin
    Fixin is a Burgundy wine appellation in eastern France known for its robust red wines made primarily from Pinot Noir.
  • B. Patch
    Patch is a surname most notably associated with Alexander Patch, a senior U.S. Army general who played a key role in World War II operations in Europe.
  • C. SFIX
    SFIX is the stock ticker symbol for Stitch Fix, an online personal styling and clothing subscription service.
  • D. Rectify
    Rectify is an American television drama series that follows a man released from death row as he struggles to reintegrate into his small Southern town and confront the unresolved questions surrounding his conviction.
  • E. Patching
    Patching is a small rural village and civil parish in West Sussex, England, situated within the South Downs and known for its scenic countryside and historic church.
  • 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: Fix
Triple: [Paul Fix, familyName, Fix]
Generated description
Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fix
Target entity description: Fix is a surname most notably associated with American character actor Paul Fix, known for his extensive work in Western films and television.
  • A. Fixin
    Fixin is a Burgundy wine appellation in eastern France known for its robust red wines made primarily from Pinot Noir.
  • B. Patch
    Patch is a surname most notably associated with Alexander Patch, a senior U.S. Army general who played a key role in World War II operations in Europe.
  • C. SFIX
    SFIX is the stock ticker symbol for Stitch Fix, an online personal styling and clothing subscription service.
  • D. Rectify
    Rectify is an American television drama series that follows a man released from death row as he struggles to reintegrate into his small Southern town and confront the unresolved questions surrounding his conviction.
  • E. Patching
    Patching is a small rural village and civil parish in West Sussex, England, situated within the South Downs and known for its scenic countryside and historic church.
  • 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_69ca848b31648190b57aa55da20285be completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9bac55b48190ab2a8f9bb83c951e completed April 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d18262dc50819089cfc17c770a1a90 completed April 4, 2026, 9:28 p.m.
NEDg Description generation batch_69d183452244819080de72fda8e14e67 completed April 4, 2026, 9:31 p.m.
NED2 Entity disambiguation (via description) batch_69d183d506b881909375aadaaa616386 completed April 4, 2026, 9:34 p.m.
Created at: March 30, 2026, 8:13 p.m.