Triple

T3214469
Position Surface form Disambiguated ID Type / Status
Subject Whiz Kids E67356 entity
Predicate notablePlayer P304 FINISHED
Object Granny Hamner
Granny Hamner was an American Major League Baseball shortstop and three-time All-Star best known for starring with the Philadelphia Phillies’ “Whiz Kids” of the early 1950s.
E337143 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: Granny Hamner | Statement: [Whiz Kids, notablePlayer, Granny Hamner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Granny Hamner
Context triple: [Whiz Kids, notablePlayer, Granny Hamner]
  • A. Dolly Sharp
    Dolly Sharp was an American adult film actress best known for her role in the landmark 1972 pornographic film "Deep Throat."
  • B. Granny
    Granny is a recurring elderly character in the Looney Tunes cartoons, best known as the kindly but sharp-witted owner of Tweety Bird (and often Sylvester’s exasperated caretaker).
  • C. Helga Cranston
    Helga Cranston was a film editor best known for her work on Laurence Olivier’s 1948 adaptation of Shakespeare’s "Hamlet."
  • D. Marcella Spruce
    Marcella Spruce is the sister of American author Tabitha King and a member of the extended King literary family.
  • E. Nannie
    Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
  • 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: Granny Hamner
Triple: [Whiz Kids, notablePlayer, Granny Hamner]
Generated description
Granny Hamner was an American Major League Baseball shortstop and three-time All-Star best known for starring with the Philadelphia Phillies’ “Whiz Kids” of the early 1950s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Granny Hamner
Target entity description: Granny Hamner was an American Major League Baseball shortstop and three-time All-Star best known for starring with the Philadelphia Phillies’ “Whiz Kids” of the early 1950s.
  • A. Dolly Sharp
    Dolly Sharp was an American adult film actress best known for her role in the landmark 1972 pornographic film "Deep Throat."
  • B. Granny
    Granny is a recurring elderly character in the Looney Tunes cartoons, best known as the kindly but sharp-witted owner of Tweety Bird (and often Sylvester’s exasperated caretaker).
  • C. Helga Cranston
    Helga Cranston was a film editor best known for her work on Laurence Olivier’s 1948 adaptation of Shakespeare’s "Hamlet."
  • D. Marcella Spruce
    Marcella Spruce is the sister of American author Tabitha King and a member of the extended King literary family.
  • E. Nannie
    Nannie is a feminine given name, often used as a diminutive or variant of names like Nancy or Anne.
  • 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_69ad858ac36c81909962589cd277d6e2 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaabd01d48190be0dc610b9987a25 completed March 8, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2623c90cc819085a94adfe3eb3f3f completed March 12, 2026, 6:50 a.m.
NEDg Description generation batch_69b2630060288190b0cf236863a5bb69 completed March 12, 2026, 6:53 a.m.
NED2 Entity disambiguation (via description) batch_69b264cbe2a48190baad7f335cdc37ba completed March 12, 2026, 7:01 a.m.
Created at: March 8, 2026, 3:07 p.m.