Triple

T1285735
Position Surface form Disambiguated ID Type / Status
Subject Lebanese American University E27428 entity
Predicate abbreviation P43 FINISHED
Object LAU
LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
 E146414 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: LAU | Statement: [Lebanese American University, abbreviation, LAU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAU
Context triple: [Lebanese American University, abbreviation, LAU]
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LAK
    LAK is the standard abbreviation used to represent the Los Angeles Lakers NBA franchise in scores, statistics, and media.
  • C. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • D. Lu
    Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
  • E. LAA
    LAA is the standard Major League Baseball abbreviation for the Los Angeles Angels franchise.
  • 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: LAU
Triple: [Lebanese American University, abbreviation, LAU]
Generated description
LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAU
Target entity description: LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
  • A. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • B. LAK
    LAK is the standard abbreviation used to represent the Los Angeles Lakers NBA franchise in scores, statistics, and media.
  • C. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • D. Lu
    Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
  • E. LAA
    LAA is the standard Major League Baseball abbreviation for the Los Angeles Angels franchise.
  • 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_69a496d4ec448190ad653b2590c46711 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b85eb48190a8b61dc397fa6390 completed March 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69aca3004b648190a4148b0421699bf9 completed March 7, 2026, 10:13 p.m.
NEDg Description generation batch_69aca3a539848190a17e8bd578bc237a completed March 7, 2026, 10:16 p.m.
NED2 Entity disambiguation (via description) batch_69aca4158bbc8190bd1f5799715e3e4c completed March 7, 2026, 10:17 p.m.
Created at: March 1, 2026, 7:51 p.m.