Triple

T1449152
Position Surface form Disambiguated ID Type / Status
Subject Leland Stanford E31248 entity
Predicate givenName P17 FINISHED
Object Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
 E171764 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: Leland | Statement: [Leland Stanford, givenName, Leland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leland
Context triple: [Leland Stanford, givenName, Leland]
  • A. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • B. Seymour
    Seymour is a small unincorporated community and suburban area in eastern Tennessee, situated near Knoxville in the foothills of the Great Smoky Mountains.
  • C. Warren
    Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
  • D. Warren
    Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
  • E. Warren
    Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
  • 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: Leland
Triple: [Leland Stanford, givenName, Leland]
Generated description
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leland
Target entity description: Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
  • A. Eldridge
    Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
  • B. Seymour
    Seymour is a small unincorporated community and suburban area in eastern Tennessee, situated near Knoxville in the foothills of the Great Smoky Mountains.
  • C. Warren
    Warren is a common English surname borne by numerous notable figures in politics, law, entertainment, and other fields.
  • D. Warren
    Warren is the given name of Warren Buffett, the renowned American investor and longtime CEO of Berkshire Hathaway.
  • E. Warren
    Warren is a large suburban city in southeast Michigan known for its extensive automotive and defense manufacturing industries.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c55c408c8190917ed44d9070a2fb completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad2328670c819087a2d8b047b67ee8 completed March 8, 2026, 7:20 a.m.
NEDg Description generation batch_69ad23ac782481909575f00ce3d7b382 completed March 8, 2026, 7:22 a.m.
NED2 Entity disambiguation (via description) batch_69ad24411d0081909ab2fab326eecd6d completed March 8, 2026, 7:24 a.m.
Created at: March 1, 2026, 8 p.m.