Triple

T15955847
Position Surface form Disambiguated ID Type / Status
Subject Salzlandkreis E386930 entity
Predicate hasLicensePlateCode P68833 FINISHED
Object SFT
SFT is the vehicle registration code used for the Salzlandkreis district in the German state of Saxony-Anhalt.
E1185890 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: SFT | Statement: [Salzlandkreis, hasLicensePlateCode, SFT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SFT
Context triple: [Salzlandkreis, hasLicensePlateCode, SFT]
  • A. SFT
    SFT is an international, student-led activist organization that campaigns for Tibetan independence and human rights in Tibet.
  • B. SHT
    SHT is the National Rail station code for Shotton railway station in Flintshire, Wales.
  • C. FT
    FT is the Faculty of Theology at the University of Geneva, a higher education institution specializing in theological and religious studies.
  • D. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • E. SIF
    SIF is a Canadian federal funding program that supports large-scale, transformative business and innovation projects to drive economic growth and competitiveness.
  • 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: SFT
Triple: [Salzlandkreis, hasLicensePlateCode, SFT]
Generated description
SFT is the vehicle registration code used for the Salzlandkreis district in the German state of Saxony-Anhalt.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SFT
Target entity description: SFT is the vehicle registration code used for the Salzlandkreis district in the German state of Saxony-Anhalt.
  • A. SFT
    SFT is an international, student-led activist organization that campaigns for Tibetan independence and human rights in Tibet.
  • B. SHT
    SHT is the National Rail station code for Shotton railway station in Flintshire, Wales.
  • C. FT
    FT is the Faculty of Theology at the University of Geneva, a higher education institution specializing in theological and religious studies.
  • D. SIF
    SIF is the governing body for ice hockey in Sweden, overseeing the national teams and domestic competitions.
  • E. SIF
    SIF is the Swiss federal body responsible for shaping and coordinating Switzerland’s international financial, tax, and monetary policy.
  • 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_69d86da882448190a82ea962fe343b79 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156fb29848190a55cabb49cb19575 completed April 16, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe7c8ef081908fa6da7975c271f6 completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf3e80b08190899262a9d03c0e93 completed May 9, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfc0d1548190b7d2e9e10e837f0b completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:53 a.m.