Triple

T22222325
Position Surface form Disambiguated ID Type / Status
Subject TfL Road Network E549241 entity
Predicate alsoKnownAs P39 FINISHED
Object TLRN
TLRN is the strategic network of major roads in London managed by Transport for London to keep traffic moving across the city.
 E1526024 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: TLRN | Statement: [TfL Road Network, alsoKnownAs, TLRN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TLRN
Context triple: [TfL Road Network, alsoKnownAs, TLRN]
  • A. TRLN
    TRLN is a collaborative consortium of research libraries in North Carolina’s Triangle region that coordinates shared resources, services, and collections.
  • B. TNRL
    TNRL is the governing body responsible for overseeing and administering rugby league activities and the national team in Tonga.
  • C. TLRA
    TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
  • D. TLN
    TLN is the IATA airport code for Toulon–Hyères Airport, a regional airport serving the Toulon area in southern France.
  • E. TL
    TL is the vehicle registration code used on license plates for vehicles registered in Tulcea County, Romania.
  • 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: TLRN
Triple: [TfL Road Network, alsoKnownAs, TLRN]
Generated description
TLRN is the strategic network of major roads in London managed by Transport for London to keep traffic moving across the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TLRN
Target entity description: TLRN is the strategic network of major roads in London managed by Transport for London to keep traffic moving across the city.
  • A. TRLN
    TRLN is a collaborative consortium of research libraries in North Carolina’s Triangle region that coordinates shared resources, services, and collections.
  • B. TNRL
    TNRL is the governing body responsible for overseeing and administering rugby league activities and the national team in Tonga.
  • C. TLRA
    TLRA was the stock ticker symbol for Telaria, a video advertising and monetization technology company that operated a programmatic platform for connected TV and digital video.
  • D. TLN
    TLN is the IATA airport code for Toulon–Hyères Airport, a regional airport serving the Toulon area in southern France.
  • E. TL
    TL is the vehicle registration code used on license plates for vehicles registered in Tulcea County, Romania.
  • 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_69e11e403d6481909a94d0aaf157f6ef completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b91f8d48190b828fcde59620ff5 completed April 28, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0aae6f44b08190b264d97b0f27b633 completed May 18, 2026, 6:15 a.m.
NEDg Description generation batch_6a0aafc850748190855c1c8d957ca913 completed May 18, 2026, 6:20 a.m.
NED2 Entity disambiguation (via description) batch_6a0ab06b29008190baf484d91039a2ba completed May 18, 2026, 6:23 a.m.
Created at: April 16, 2026, 8:37 p.m.