Triple

T7469230
Position Surface form Disambiguated ID Type / Status
Subject Frackville, Pennsylvania E176462 entity
Predicate namedAfter P63 FINISHED
Object Daniel Frack
Daniel Frack was an early local figure and landowner after whom the borough of Frackville, Pennsylvania, was named.
 E667284 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: Daniel Frack | Statement: [Frackville, Pennsylvania, namedAfter, Daniel Frack]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Daniel Frack
Context triple: [Frackville, Pennsylvania, namedAfter, Daniel Frack]
  • A. David Frisch
    David Frisch is a former American football wide receiver who played in the National Football League during the 1990s.
  • B. Robert Frazen
    Robert Frazen is a film editor known for his work on movies such as "Smokin' Aces."
  • C. Dan Frazer
    Dan Frazer was an American character actor best known for his role as Captain Frank McNeil on the television series "Kojak."
  • D. Daniel Roher
    Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
  • E. Daniel Francis
    Daniel Francis was a prominent figure after whom the city of Francistown in Botswana was named, likely due to his significant role in the region’s early development or history.
  • 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: Daniel Frack
Triple: [Frackville, Pennsylvania, namedAfter, Daniel Frack]
Generated description
Daniel Frack was an early local figure and landowner after whom the borough of Frackville, Pennsylvania, was named.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Daniel Frack
Target entity description: Daniel Frack was an early local figure and landowner after whom the borough of Frackville, Pennsylvania, was named.
  • A. David Frisch
    David Frisch is a former American football wide receiver who played in the National Football League during the 1990s.
  • B. Robert Frazen
    Robert Frazen is a film editor known for his work on movies such as "Smokin' Aces."
  • C. Dan Frazer
    Dan Frazer was an American character actor best known for his role as Captain Frank McNeil on the television series "Kojak."
  • D. Daniel Roher
    Daniel Roher is a Canadian documentary filmmaker best known for directing the Oscar-winning political documentary "Navalny."
  • E. Daniel Francis
    Daniel Francis was a prominent figure after whom the city of Francistown in Botswana was named, likely due to his significant role in the region’s early development or history.
  • 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_69c69f223fd88190b4c69b95d7cbeeda completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3f845e081908117783ff1e63e23 completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83475392c8190a51d24e1530c0c83 completed March 28, 2026, 8:05 p.m.
NEDg Description generation batch_69c835ce5bbc8190b968535c16cfc660 completed March 28, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_69c836a80eb081908b9937944fe18661 completed March 28, 2026, 8:14 p.m.
Created at: March 27, 2026, 3:41 p.m.