Triple

T14008755
Position Surface form Disambiguated ID Type / Status
Subject South Eastern University of Sri Lanka E337020 entity
Predicate abbreviation P43 FINISHED
Object SEUSL
SEUSL is a public university in Sri Lanka’s Eastern Province known for providing higher education and research opportunities across a range of disciplines.
 E1074429 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: SEUSL | Statement: [South Eastern University of Sri Lanka, abbreviation, SEUSL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEUSL
Context triple: [South Eastern University of Sri Lanka, abbreviation, SEUSL]
  • A. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • B. Sel
    Sel is a municipality in Innlandet county, Norway, known for its mountainous landscapes and location in the Gudbrandsdalen valley.
  • C. SEBL
    SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
  • D. SEST
    SEST is the ICAO airport code for San Cristóbal Airport, which serves San Cristóbal Island in the Galápagos, Ecuador.
  • E. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • 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: SEUSL
Triple: [South Eastern University of Sri Lanka, abbreviation, SEUSL]
Generated description
SEUSL is a public university in Sri Lanka’s Eastern Province known for providing higher education and research opportunities across a range of disciplines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEUSL
Target entity description: SEUSL is a public university in Sri Lanka’s Eastern Province known for providing higher education and research opportunities across a range of disciplines.
  • A. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • B. Sel
    Sel is a municipality in Innlandet county, Norway, known for its mountainous landscapes and location in the Gudbrandsdalen valley.
  • C. SEBL
    SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
  • D. SEST
    SEST is the ICAO airport code for San Cristóbal Airport, which serves San Cristóbal Island in the Galápagos, Ecuador.
  • E. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • 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_69d81c645c5c8190b1fd16a285a1b78a completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ed44f90819099ad08c09c066b56 completed April 14, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbaca5fb48819090fff1fd22e8a15c completed May 6, 2026, 9:03 p.m.
NEDg Description generation batch_69fbadc6cb2c8190bdf66ad1fa6dd392 completed May 6, 2026, 9:08 p.m.
NED2 Entity disambiguation (via description) batch_69fbb01071408190a85e5e9be0150593 completed May 6, 2026, 9:18 p.m.
Created at: April 9, 2026, 10:19 p.m.