Triple

T1828419
Position Surface form Disambiguated ID Type / Status
Subject Government’s Foreign and Security Policy Committee E40706 entity
Predicate shortName P43 FINISHED
Object TP-UTVA
TP-UTVA is the abbreviated name for the Government’s Foreign and Security Policy Committee, a key body responsible for shaping and coordinating Finland’s foreign and security policy.
 E203348 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: TP-UTVA | Statement: [Government’s Foreign and Security Policy Committee, shortName, TP-UTVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TP-UTVA
Context triple: [Government’s Foreign and Security Policy Committee, shortName, TP-UTVA]
  • A. KTPA
    KTPA is the ICAO airport code for Tampa International Airport, a major commercial aviation hub serving the Tampa Bay area in Florida, USA.
  • B. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • C. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • D. LTU
    LTU is the three-letter ISO 3166-1 alpha-3 country code assigned to Lithuania.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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: TP-UTVA
Triple: [Government’s Foreign and Security Policy Committee, shortName, TP-UTVA]
Generated description
TP-UTVA is the abbreviated name for the Government’s Foreign and Security Policy Committee, a key body responsible for shaping and coordinating Finland’s foreign and security policy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TP-UTVA
Target entity description: TP-UTVA is the abbreviated name for the Government’s Foreign and Security Policy Committee, a key body responsible for shaping and coordinating Finland’s foreign and security policy.
  • A. KTPA
    KTPA is the ICAO airport code for Tampa International Airport, a major commercial aviation hub serving the Tampa Bay area in Florida, USA.
  • B. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • C. TNUA
    TNUA is an academic association or network that includes Nagoya University among its member institutions.
  • D. LTU
    LTU is the three-letter ISO 3166-1 alpha-3 country code assigned to Lithuania.
  • E. UCA
    UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
  • 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_69a8864644bc8190b2358ab897194ac1 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb01191208190a7eaf3036638ec40 completed March 7, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6b4bdc8190b53dbdc9c31e3685 completed March 8, 2026, 6:26 p.m.
NEDg Description generation batch_69adc07fff60819092b10dd0e417ac5a completed March 8, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69adc0fd79c48190864f53a90517edc6 completed March 8, 2026, 6:33 p.m.
Created at: March 4, 2026, 7:32 p.m.