Triple

T15333194
Position Surface form Disambiguated ID Type / Status
Subject Sedgwick E366592 entity
Predicate hasCTAStationCode P1289 FINISHED
Object SED
SED is the CTA station code for the Sedgwick station on Chicago’s 'L' rapid transit system.
E1151691 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: SED | Statement: [Sedgwick, hasCTAStationCode, SED]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SED
Context triple: [Sedgwick, hasCTAStationCode, SED]
  • A. SED
    SED was the ruling Marxist–Leninist party that governed East Germany (the German Democratic Republic) from its founding in 1949 until the end of communist rule in 1989.
  • B. SER
    SER is the commonly used abbreviation for South Eastern Railway, a major railway zone in India.
  • C. SE-D
    SE-D is the ISO 3166-2 regional code assigned to Dalarna County in Sweden.
  • D. SES
    SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
  • E. SES
    SES is the abbreviation for the Senior Executive Service, the corps of top-level civilian managers and executives in the U.S. federal government.
  • 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: SED
Triple: [Sedgwick, hasCTAStationCode, SED]
Generated description
SED is the CTA station code for the Sedgwick station on Chicago’s 'L' rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SED
Target entity description: SED is the CTA station code for the Sedgwick station on Chicago’s 'L' rapid transit system.
  • A. SED
    SED was the ruling Marxist–Leninist party that governed East Germany (the German Democratic Republic) from its founding in 1949 until the end of communist rule in 1989.
  • B. SER
    SER is the commonly used abbreviation for South Eastern Railway, a major railway zone in India.
  • C. SE-D
    SE-D is the ISO 3166-2 regional code assigned to Dalarna County in Sweden.
  • D. SES
    SES is the abbreviation for the Senior Executive Service, the corps of top-level civilian managers and executives in the U.S. federal government.
  • E. SES
    SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e0268608190947a58f559a67717 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01ecb904819082454622dcd77556 completed May 9, 2026, 9:44 a.m.
NEDg Description generation batch_69ff03d4432c8190af9ce13c0ff70a36 completed May 9, 2026, 9:52 a.m.
NED2 Entity disambiguation (via description) batch_69ff044e01308190b2f077aecae1eece completed May 9, 2026, 9:54 a.m.
Created at: April 10, 2026, 3:17 a.m.