Triple

T2589304
Position Surface form Disambiguated ID Type / Status
Subject Walsh School of Foreign Service E58080 entity
Predicate shortName P43 FINISHED
Object SFS
SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
 E278620 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: SFS | Statement: [Walsh School of Foreign Service, shortName, SFS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SFS
Context triple: [Walsh School of Foreign Service, shortName, SFS]
  • A. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • B. SF
    SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
  • C. SFM
    SFM is the station code for San Francisco's 4th and King Street Caltrain terminal, a major commuter rail hub in the city.
  • D. FFS
    FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
  • E. SDF
    SDF is the acronym for the SAARC Development Fund, a regional financial institution that supports social, economic, and infrastructure development projects among South Asian Association for Regional Cooperation member countries.
  • 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: SFS
Triple: [Walsh School of Foreign Service, shortName, SFS]
Generated description
SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SFS
Target entity description: SFS is a renowned Georgetown University school specializing in international affairs, diplomacy, and global policy education.
  • A. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • B. SF
    SF is the standard two-letter postal abbreviation used to represent the city of San Francisco, California.
  • C. SFM
    SFM is the station code for San Francisco's 4th and King Street Caltrain terminal, a major commuter rail hub in the city.
  • D. FFS
    FFS is the commonly used abbreviation for the Swiss Federal Railways, the national railway company of Switzerland.
  • E. SDF
    SDF is the acronym for the SAARC Development Fund, a regional financial institution that supports social, economic, and infrastructure development projects among South Asian Association for Regional Cooperation member countries.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd3feb45c81909369a49c3990294a completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af658782f88190a83a4f7256d6a7b2 completed March 10, 2026, 12:27 a.m.
NEDg Description generation batch_69af660bc6cc8190a98dca9632d5635d completed March 10, 2026, 12:30 a.m.
NED2 Entity disambiguation (via description) batch_69af667f0458819091d88011f49dc1ae completed March 10, 2026, 12:31 a.m.
Created at: March 6, 2026, 9:49 p.m.