Triple

T5249872
Position Surface form Disambiguated ID Type / Status
Subject Frances Bavier E118559 entity
Predicate familyName P18 FINISHED
Object Bavier
Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
 E508504 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: Bavier | Statement: [Frances Bavier, familyName, Bavier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bavier
Context triple: [Frances Bavier, familyName, Bavier]
  • A. Starnberg
    Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
  • B. Schwarzenberg
    Schwarzenberg is the noble family name of a prominent Central European princely house historically influential in Austrian and Bohemian politics and military affairs.
  • C. Bardenbach
    Bardenbach is a village and district of the town of Wadern in the Saarland region of western Germany.
  • D. Idstein
    Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
  • E. Sieber
    Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
  • 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: Bavier
Triple: [Frances Bavier, familyName, Bavier]
Generated description
Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bavier
Target entity description: Bavier is the surname of Frances Bavier, the American actress best known for playing Aunt Bee on the classic television series "The Andy Griffith Show."
  • A. Starnberg
    Starnberg is a lakeside town in Bavaria, Germany, known for its affluent residential character and scenic location on Lake Starnberg southwest of Munich.
  • B. Schwarzenberg
    Schwarzenberg is the noble family name of a prominent Central European princely house historically influential in Austrian and Bohemian politics and military affairs.
  • C. Bardenbach
    Bardenbach is a village and district of the town of Wadern in the Saarland region of western Germany.
  • D. Idstein
    Idstein is a historic town in the German state of Hesse, known for its well-preserved medieval old town and timber-framed architecture.
  • E. Sieber
    Sieber is a small river in the German state of Lower Saxony that flows through the Harz Mountains and into the Oder.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b787b34819081af96de9355bb4f completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06bc1c0c8190abc1e24f99621e49 completed March 21, 2026, 8:59 p.m.
NEDg Description generation batch_69bf098637148190ab999486de995ee4 completed March 21, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69bf0a1675b8819084024aa2a99ec843 completed March 21, 2026, 9:13 p.m.
Created at: March 20, 2026, 1:50 p.m.