Triple

T1720313
Position Surface form Disambiguated ID Type / Status
Subject Helsinki University of Technology E37373 entity
Predicate hasAbbreviation P43 FINISHED
Object TKK
TKK is the former Helsinki University of Technology, a major Finnish institution known for its engineering and technology education and research.
 E193892 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: TKK | Statement: [Helsinki University of Technology, hasAbbreviation, TKK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TKK
Context triple: [Helsinki University of Technology, hasAbbreviation, TKK]
  • A. SKK
    SKK was the ISO 4217 currency code for the Slovak koruna, the former official currency of Slovakia before adoption of the euro.
  • B. TKM
    TKM is the three-letter ISO 3166-1 alpha-3 country code assigned to Turkmenistan.
  • C. KKL
    KKL is the Hebrew acronym for Keren Kayemeth LeIsrael, the Jewish National Fund organization known for land development, afforestation, and environmental projects in Israel.
  • D. K.T.S.E.
    K.T.S.E. is Teyana Taylor’s critically acclaimed 2018 R&B album known for its soulful production and emotionally candid songwriting.
  • E. TFF
    TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
  • 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: TKK
Triple: [Helsinki University of Technology, hasAbbreviation, TKK]
Generated description
TKK is the former Helsinki University of Technology, a major Finnish institution known for its engineering and technology education and research.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TKK
Target entity description: TKK is the former Helsinki University of Technology, a major Finnish institution known for its engineering and technology education and research.
  • A. SKK
    SKK was the ISO 4217 currency code for the Slovak koruna, the former official currency of Slovakia before adoption of the euro.
  • B. TKM
    TKM is the three-letter ISO 3166-1 alpha-3 country code assigned to Turkmenistan.
  • C. KKL
    KKL is the Hebrew acronym for Keren Kayemeth LeIsrael, the Jewish National Fund organization known for land development, afforestation, and environmental projects in Israel.
  • D. K.T.S.E.
    K.T.S.E. is Teyana Taylor’s critically acclaimed 2018 R&B album known for its soulful production and emotionally candid songwriting.
  • E. TFF
    TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
  • 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_69a8861912dc8190931af43b4b9158a7 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa63558d7c8190830cb8ee2e4a8932 completed March 6, 2026, 5:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8ae98cd88190af4dc46679b3d93f completed March 8, 2026, 2:42 p.m.
NEDg Description generation batch_69ad957bd63c819099a508ca5c4102cc completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97b18f9c8190a9c5ed80b5ed0195 completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:30 p.m.