Triple

T18265809
Position Surface form Disambiguated ID Type / Status
Subject PK E437479 entity
Predicate relatedFormat P26987 FINISHED
Object TFM
TFM is a font metric file format used primarily by TeX to store information about character dimensions and font layout.
 E1315950 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: TFM | Statement: [PK, relatedFormat, TFM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TFM
Context triple: [PK, relatedFormat, TFM]
  • A. TFB
    TFB is the acronym commonly used to refer to the Task Force Bureau, an organized body typically responsible for coordinating specialized operations or initiatives.
  • B. TfWM
    TfWM is the public transport authority responsible for planning, coordinating, and improving transport services across the West Midlands region of England.
  • C. LTFM
    LTFM is the ICAO airport code for Istanbul Airport, the main international airport serving Istanbul, Turkey.
  • D. TFR
    TFR is the state-owned freight rail division of Transnet that operates and manages South Africa’s national rail freight network.
  • E. TFI
    TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
  • 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: TFM
Triple: [PK, relatedFormat, TFM]
Generated description
TFM is a font metric file format used primarily by TeX to store information about character dimensions and font layout.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TFM
Target entity description: TFM is a font metric file format used primarily by TeX to store information about character dimensions and font layout.
  • A. TFB
    TFB is the acronym commonly used to refer to the Task Force Bureau, an organized body typically responsible for coordinating specialized operations or initiatives.
  • B. TfWM
    TfWM is the public transport authority responsible for planning, coordinating, and improving transport services across the West Midlands region of England.
  • C. LTFM
    LTFM is the ICAO airport code for Istanbul Airport, the main international airport serving Istanbul, Turkey.
  • D. TFR
    TFR is the state-owned freight rail division of Transnet that operates and manages South Africa’s national rail freight network.
  • E. TFI
    TFI is the World Health Organization’s Tobacco Free Initiative, a program dedicated to reducing global tobacco use and its health impacts.
  • 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_69d8b913351c8190932b6a426de04b41 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ff79851481909a4bbeb14fb00647 completed April 19, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03b3f6c1b081908fdd0ccb6f1bf633 completed May 12, 2026, 11:12 p.m.
NEDg Description generation batch_6a03b4f0cd188190a9577a3999a5b473 completed May 12, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_6a03b5c09f4881909fb0ead5fc48895c completed May 12, 2026, 11:20 p.m.
Created at: April 10, 2026, 10:34 a.m.