Triple

T8482279
Position Surface form Disambiguated ID Type / Status
Subject Lee Sedol E200548 entity
Predicate givenName P17 FINISHED
Object Sedol
Sedol is the given name of Lee Sedol, the renowned South Korean professional Go player known for his historic matches against AI.
 E736776 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: Sedol | Statement: [Lee Sedol, givenName, Sedol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sedol
Context triple: [Lee Sedol, givenName, Sedol]
  • A. Fama
    Fama is the surname of Eugene Fama, a Nobel Prize–winning American economist renowned for his work on efficient markets and asset pricing.
  • B. Blackrock
    Blackrock is a suburban residential area of Cork city in County Cork, Ireland, known for its riverside location along the River Lee and historic maritime and industrial heritage.
  • C. Hulbert
    Hulbert is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
  • D. Tobin
    Tobin is the given name of Tobin Heath, an American professional soccer player and multiple-time FIFA Women's World Cup champion.
  • E. Templeton
    Templeton is the gluttonous, self-serving rat from E.B. White’s "Charlotte’s Web," known for his comic relief and pivotal role in helping save Wilbur the pig.
  • 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: Sedol
Triple: [Lee Sedol, givenName, Sedol]
Generated description
Sedol is the given name of Lee Sedol, the renowned South Korean professional Go player known for his historic matches against AI.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sedol
Target entity description: Sedol is the given name of Lee Sedol, the renowned South Korean professional Go player known for his historic matches against AI.
  • A. Fama
    Fama is the surname of Eugene Fama, a Nobel Prize–winning American economist renowned for his work on efficient markets and asset pricing.
  • B. Blackrock
    Blackrock is a suburban residential area of Cork city in County Cork, Ireland, known for its riverside location along the River Lee and historic maritime and industrial heritage.
  • C. Hulbert
    Hulbert is a small rural community located within the Township of South Dundas in eastern Ontario, Canada.
  • D. Tobin
    Tobin is the given name of Tobin Heath, an American professional soccer player and multiple-time FIFA Women's World Cup champion.
  • E. Templeton
    Templeton is the gluttonous, self-serving rat from E.B. White’s "Charlotte’s Web," known for his comic relief and pivotal role in helping save Wilbur the pig.
  • 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_69ca831b17988190a1f3f3413d57b820 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe53638c48190b742fc51d1b4442a completed March 31, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce3a2b2e9081909f19712946c6ec20 completed April 2, 2026, 9:43 a.m.
NEDg Description generation batch_69ce3b4008a0819096bb44b46f510213 completed April 2, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69ce3c000e608190adf1b6499d382529 completed April 2, 2026, 9:50 a.m.
Created at: March 30, 2026, 6:12 p.m.