Triple

T9473317
Position Surface form Disambiguated ID Type / Status
Subject Triangle Research Libraries Network E228447 entity
Predicate hasAbbreviation P43 FINISHED
Object TRLN
TRLN is a collaborative consortium of research libraries in North Carolina’s Triangle region that coordinates shared resources, services, and collections.
 E801416 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: TRLN | Statement: [Triangle Research Libraries Network, hasAbbreviation, TRLN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TRLN
Context triple: [Triangle Research Libraries Network, hasAbbreviation, TRLN]
  • A. TNRL
    TNRL is the governing body responsible for overseeing and administering rugby league activities and the national team in Tonga.
  • B. TLN
    TLN is the IATA airport code for Toulon–Hyères Airport, a regional airport serving the Toulon area in southern France.
  • C. TRN
    TRN is the IATA airport code for Turin Airport, the main international airport serving Turin in northern Italy.
  • D. LTN
    LTN is the IATA airport code for London Luton Airport, a major international airport serving the London metropolitan area in the United Kingdom.
  • E. TRL
    TRL is a popular abbreviation for "Total Request Live," a former MTV music video countdown show that became a major pop culture phenomenon in the late 1990s and early 2000s.
  • 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: TRLN
Triple: [Triangle Research Libraries Network, hasAbbreviation, TRLN]
Generated description
TRLN is a collaborative consortium of research libraries in North Carolina’s Triangle region that coordinates shared resources, services, and collections.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TRLN
Target entity description: TRLN is a collaborative consortium of research libraries in North Carolina’s Triangle region that coordinates shared resources, services, and collections.
  • A. TNRL
    TNRL is the governing body responsible for overseeing and administering rugby league activities and the national team in Tonga.
  • B. TLN
    TLN is the IATA airport code for Toulon–Hyères Airport, a regional airport serving the Toulon area in southern France.
  • C. TRN
    TRN is the IATA airport code for Turin Airport, the main international airport serving Turin in northern Italy.
  • D. LTN
    LTN is the IATA airport code for London Luton Airport, a major international airport serving the London metropolitan area in the United Kingdom.
  • E. TRL
    TRL is a popular abbreviation for "Total Request Live," a former MTV music video countdown show that became a major pop culture phenomenon in the late 1990s and early 2000s.
  • 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_69ca847162c48190b079076c9595513c completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7ff0afd08190871b68a88fdbff2b completed April 1, 2026, 8:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69d122d625fc8190b8222930449ad3da completed April 4, 2026, 2:40 p.m.
NEDg Description generation batch_69d12395841c8190857de8a50ab6345c completed April 4, 2026, 2:43 p.m.
NED2 Entity disambiguation (via description) batch_69d1275bcbd88190a5742a9cf802425a completed April 4, 2026, 2:59 p.m.
Created at: March 30, 2026, 7:54 p.m.