Triple

T27247246
Position Surface form Disambiguated ID Type / Status
Subject Clement Calhoun Young E687376 entity
Predicate lieutenantGovernorDuringTerm P162276 FINISHED
Object Burton M. Green
Burton M. Green was an American businessman and real estate developer best known for his role in founding and developing Beverly Hills, California.
 E1787677 NE FINISHED

How this triple was built (3 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: Burton M. Green | Statement: [Clement Calhoun Young, lieutenantGovernorDuringTerm, Burton M. Green]
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: Burton M. Green
Triple: [Clement Calhoun Young, lieutenantGovernorDuringTerm, Burton M. Green]
Generated description
Burton M. Green was an American businessman and real estate developer best known for his role in founding and developing Beverly Hills, California.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: lieutenantGovernorDuringTerm
Context triple: [Clement Calhoun Young, lieutenantGovernorDuringTerm, Burton M. Green]
  • A. servedAsGovernorUntil
    Indicates that an entity held the position of governor up to a specified end date or time.
  • B. governorTerm
    Indicates the time period during which a person holds or held the office of governor of a specific jurisdiction.
  • C. builtDuringGovernorshipOf
    Indicates that the construction of one entity occurred during the period when another entity held a governing office.
  • D. lieutenantGovernorElected
    Indicates that an individual attains the position of lieutenant governor through an electoral process.
  • E. laterGovernor
    Indicates that one entity subsequently became the governor of a place or jurisdiction associated with another entity.
  • F. None of above. chosen

Provenance (7 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_69ef355547408190b5ca0d777c65040a completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626b2ba8c819090a9eb67cf9cb701 completed May 2, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e4339b8c8190a4a8898f14807e67 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4bc42e081909864bb2839e08143 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e551ec288190b818e25bf2e62f45 completed May 24, 2026, 11:47 a.m.
PD Predicate disambiguation batch_69f620e38aec8190bb184edcdbd6da64 completed May 2, 2026, 4:05 p.m.
PDg Predicate description generation batch_69f622a8fe7c819096e8a43db263a423 completed May 2, 2026, 4:13 p.m.
Created at: April 27, 2026, 10:42 a.m.