Triple

T413900
Position Surface form Disambiguated ID Type / Status
Subject Transport for Greater Manchester E9548 entity
Predicate abbreviation P43 FINISHED
Object TfGM
TfGM is the public body responsible for planning, coordinating, and improving public transport and related infrastructure across the Greater Manchester region in England.
 E52498 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: TfGM | Statement: [Transport for Greater Manchester, abbreviation, TfGM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TfGM
Context triple: [Transport for Greater Manchester, abbreviation, TfGM]
  • A. Manf
    Manf is the Arabic name for the ancient Egyptian city of Memphis, a historically significant capital near modern-day Cairo.
  • B. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • C. TFF
    TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
  • D. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • E. TOTEM
    TOTEM is a high-energy physics experiment at CERN’s Large Hadron Collider that precisely measures proton–proton scattering and total cross sections.
  • 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: TfGM
Triple: [Transport for Greater Manchester, abbreviation, TfGM]
Generated description
TfGM is the public body responsible for planning, coordinating, and improving public transport and related infrastructure across the Greater Manchester region in England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TfGM
Target entity description: TfGM is the public body responsible for planning, coordinating, and improving public transport and related infrastructure across the Greater Manchester region in England.
  • A. Manf
    Manf is the Arabic name for the ancient Egyptian city of Memphis, a historically significant capital near modern-day Cairo.
  • B. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • C. TFF
    TFF is a renowned annual film festival held in Telluride, Colorado, known for premiering critically acclaimed and award-contending films.
  • D. the T
    The T is the public transit system serving the Greater Boston area, operated by the Massachusetts Bay Transportation Authority.
  • E. TOTEM
    TOTEM is a high-energy physics experiment at CERN’s Large Hadron Collider that precisely measures proton–proton scattering and total cross sections.
  • 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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecdd3d1c8190a31b071569cfc980 completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41b4ce1648190b1f46ba33d7cf946 completed March 1, 2026, 10:56 a.m.
NEDg Description generation batch_69a41bc18b388190ae97d97656294e7b completed March 1, 2026, 10:58 a.m.
NED2 Entity disambiguation (via description) batch_69a422983e708190904cd891d3996338 completed March 1, 2026, 11:27 a.m.
Created at: Feb. 28, 2026, 1:09 p.m.