Triple

T4900124
Position Surface form Disambiguated ID Type / Status
Subject Bluebook legal citation E109776 entity
Predicate hasComponent P35 FINISHED
Object Whitepages
Whitepages is a widely used online directory service that provides contact and background information on individuals and businesses.
 E478392 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: Whitepages | Statement: [Bluebook legal citation, hasComponent, Whitepages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Whitepages
Context triple: [Bluebook legal citation, hasComponent, Whitepages]
  • A. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • B. Dawson
    Dawson is a common English-language surname of Anglo-Saxon origin, meaning "son of David."
  • C. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • D. Everette
    Everette is the given first name of E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
  • E. Mahlon
    Mahlon is a minor biblical figure in the Book of Ruth, known as one of Naomi’s sons and the first husband of Ruth.
  • 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: Whitepages
Triple: [Bluebook legal citation, hasComponent, Whitepages]
Generated description
Whitepages is a widely used online directory service that provides contact and background information on individuals and businesses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Whitepages
Target entity description: Whitepages is a widely used online directory service that provides contact and background information on individuals and businesses.
  • A. Leland
    Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • B. Dawson
    Dawson is a common English-language surname of Anglo-Saxon origin, meaning "son of David."
  • C. Blaine
    Blaine is a small coastal city in northwestern Washington State, located near the Canadian border.
  • D. Everette
    Everette is the given first name of E. Howard Hunt, the American intelligence officer and author involved in the Watergate scandal.
  • E. Mahlon
    Mahlon is a minor biblical figure in the Book of Ruth, known as one of Naomi’s sons and the first husband of Ruth.
  • 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_69bd4410bbf88190aad50d2451c863d6 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e4c9a788190aaceec00d0057143 completed March 20, 2026, 3:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fcda9748190a5101aed11ae14a8 completed March 21, 2026, 10:15 a.m.
NEDg Description generation batch_69be707405008190ba1456544e8da593 completed March 21, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69be70e5537c8190b4db230932818a9c completed March 21, 2026, 10:20 a.m.
Created at: March 20, 2026, 1:28 p.m.