Triple

T13904545
Position Surface form Disambiguated ID Type / Status
Subject Graduate School of Social Work E334311 entity
Predicate shortName P43 FINISHED
Object GSSW
GSSW is an academic institution focused on graduate-level education and research in social work and related social justice fields.
 E1067658 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: GSSW | Statement: [Graduate School of Social Work, shortName, GSSW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GSSW
Context triple: [Graduate School of Social Work, shortName, GSSW]
  • A. SWU
    SWU is the commonly used abbreviation for Southwest University, a comprehensive higher education institution in China.
  • B. SWK
    SWK is the National Rail station code for Southwark railway station in London.
  • C. WSSS
    WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
  • D. WSW
    WSW is a professional football club based in Western Sydney, Australia, competing in the A-League Men.
  • E. WSW
    WSW is the National Rail station code assigned to Wandsworth Common railway station in London, England.
  • 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: GSSW
Triple: [Graduate School of Social Work, shortName, GSSW]
Generated description
GSSW is an academic institution focused on graduate-level education and research in social work and related social justice fields.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GSSW
Target entity description: GSSW is an academic institution focused on graduate-level education and research in social work and related social justice fields.
  • A. SWU
    SWU is the commonly used abbreviation for Southwest University, a comprehensive higher education institution in China.
  • B. SWK
    SWK is the National Rail station code for Southwark railway station in London.
  • C. WSSS
    WSSS is the ICAO airport code for Singapore Changi Airport, one of the world’s busiest and most highly rated international air hubs.
  • D. WSW
    WSW is a professional football club based in Western Sydney, Australia, competing in the A-League Men.
  • E. WSW
    WSW is the National Rail station code assigned to Wandsworth Common railway station in London, England.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de25db1e308190aaed6a21e443cc44 completed April 14, 2026, 11:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c724c6188190ae0c2784c3b48a12 completed May 3, 2026, 10:07 p.m.
NEDg Description generation batch_69f7c7e1247481908073c1e282c3619f completed May 3, 2026, 10:10 p.m.
NED2 Entity disambiguation (via description) batch_69f7c8f2b5588190b6143d676eb648a0 completed May 3, 2026, 10:15 p.m.
Created at: April 9, 2026, 10:16 p.m.