Triple

T1328886
Position Surface form Disambiguated ID Type / Status
Subject Tifinagh E28394 entity
Predicate ISO15924Code P208 FINISHED
Object Tfng
Tfng is the ISO 15924 four-letter code assigned to the Tifinagh script used for writing various Berber (Amazigh) languages.
E151665 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: Tfng | Statement: [Tifinagh, ISO15924Code, Tfng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tfng
Context triple: [Tifinagh, ISO15924Code, Tfng]
  • A. TfGM
    TfGM is the public body responsible for planning, coordinating, and improving public transport and related infrastructure across the Greater Manchester region in England.
  • B. TFI
    TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
  • C. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • D. T5
    T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
  • E. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • 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: Tfng
Triple: [Tifinagh, ISO15924Code, Tfng]
Generated description
Tfng is the ISO 15924 four-letter code assigned to the Tifinagh script used for writing various Berber (Amazigh) languages.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tfng
Target entity description: Tfng is the ISO 15924 four-letter code assigned to the Tifinagh script used for writing various Berber (Amazigh) languages.
  • A. TfGM
    TfGM is the public body responsible for planning, coordinating, and improving public transport and related infrastructure across the Greater Manchester region in England.
  • B. TFI
    TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
  • C. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • D. T5
    T5 is a major passenger terminal at London Heathrow Airport, primarily serving British Airways and Iberia flights.
  • E. TU
    TU is the international vehicle registration code assigned to Tunisia.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1c30c948190afc6342b3dcda948 completed March 1, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf32b488819095dc63d338a30b9b completed March 8, 2026, 12:13 a.m.
NEDg Description generation batch_69acbfc03f20819089a025fc745c9203 completed March 8, 2026, 12:16 a.m.
NED2 Entity disambiguation (via description) batch_69acc0282080819087676813c2852a96 completed March 8, 2026, 12:17 a.m.
Created at: March 1, 2026, 7:55 p.m.