Triple

T8317192
Position Surface form Disambiguated ID Type / Status
Subject Larry King (attorney) E194734 entity
Predicate hasFamilyName P18 FINISHED
Object King
King is a common English surname historically associated with people who worked for or represented the monarchy, and now borne by many individuals worldwide across diverse professions.
 E1611 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: King | Statement: [Larry King (attorney), hasFamilyName, King]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: King
Context triple: [Larry King (attorney), hasFamilyName, King]
  • A. King
    The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
  • B. King
    King is a township in the Regional Municipality of York in Ontario, Canada, known for its rural landscapes, rolling hills, and equestrian farms within the Greater Toronto Area.
  • C. King
    The King of Norway is the constitutional monarch and ceremonial head of state in Norway’s parliamentary system.
  • D. King
    King is a prominent video game company best known for creating the massively popular mobile puzzle game Candy Crush Saga.
  • E. King
    King is a public transit stop commonly associated with King Street, likely serving as a key access point along that corridor.
  • 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: King
Triple: [Larry King (attorney), hasFamilyName, King]
Generated description
King is a common English surname historically associated with people who worked for or represented the monarchy, and now borne by many individuals worldwide across diverse professions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: King
Target entity description: King is a common English surname historically associated with people who worked for or represented the monarchy, and now borne by many individuals worldwide across diverse professions.
  • A. King
    King is a masculine given name, historically associated with leadership or nobility and occasionally used as a first name in English-speaking countries.
  • B. King
    King is a regal title traditionally denoting a male sovereign ruler of a kingdom, often associated with supreme authority and hereditary monarchy.
  • C. King chosen
    King is a common English surname borne by numerous notable figures, including civil rights leader Martin Luther King Jr.
  • D. King
    The King is the reigning male monarch who serves as the head of state of the United Kingdom within its constitutional monarchy system.
  • E. King
    King is a professional esports player best known for competing under the handle "King" in games such as League of Legends.
  • F. None of above.

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_69ca82e6e2648190a31eaf6f4f757b2a completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f630ea881909fb639383e60aee9 completed March 31, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd958cf0808190af59e36c35b91e58 completed April 1, 2026, 10 p.m.
NEDg Description generation batch_69cdab5f30b0819080136084d81774a9 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2d365e48190a766ca959ce56b19 completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:55 p.m.