Triple

T16910519
Position Surface form Disambiguated ID Type / Status
Subject Tyler Junior College E410180 entity
Predicate hasNickname P39 FINISHED
Object TJC
TJC is a public community college in Tyler, Texas, offering two-year academic and technical programs as well as workforce training.
 E1239772 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: TJC | Statement: [Tyler Junior College, hasNickname, TJC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TJC
Context triple: [Tyler Junior College, hasNickname, TJC]
  • A. TJC
    TJC is a U.S.-based nonprofit organization that accredits and certifies healthcare organizations and programs to promote quality and patient safety.
  • B. TJNR
    TJNR is the ICAO airport code for José Aponte de la Torre Airport in Ceiba, Puerto Rico.
  • C. TJCP
    TJCP is the ICAO airport code assigned to Benjamin Rivera Noriega Airport in Puerto Rico.
  • D. TNCM
    TNCM is the ICAO airport code for Princess Juliana International Airport, the major international gateway to the Caribbean island of Sint Maarten, famous for its runway’s close proximity to Maho Beach.
  • E. J-TREC
    J-TREC (Japan Transport Engineering Company) is a Japanese rolling stock manufacturer known for producing a wide range of commuter and regional trains for rail operators such as JR East.
  • 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: TJC
Triple: [Tyler Junior College, hasNickname, TJC]
Generated description
TJC is a public community college in Tyler, Texas, offering two-year academic and technical programs as well as workforce training.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TJC
Target entity description: TJC is a public community college in Tyler, Texas, offering two-year academic and technical programs as well as workforce training.
  • A. TJC
    TJC is a U.S.-based nonprofit organization that accredits and certifies healthcare organizations and programs to promote quality and patient safety.
  • B. TJNR
    TJNR is the ICAO airport code for José Aponte de la Torre Airport in Ceiba, Puerto Rico.
  • C. TJCP
    TJCP is the ICAO airport code assigned to Benjamin Rivera Noriega Airport in Puerto Rico.
  • D. TNCM
    TNCM is the ICAO airport code for Princess Juliana International Airport, the major international gateway to the Caribbean island of Sint Maarten, famous for its runway’s close proximity to Maho Beach.
  • E. J-TREC
    J-TREC (Japan Transport Engineering Company) is a Japanese rolling stock manufacturer known for producing a wide range of commuter and regional trains for rail operators such as JR East.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3ca0c481909ff361ccf4a922e3 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7bb4ac481909318d3d61a2d10e1 completed May 10, 2026, 6 p.m.
NEDg Description generation batch_6a00c8c9c78481908e503977d47f7c1f completed May 10, 2026, 6:04 p.m.
NED2 Entity disambiguation (via description) batch_6a00c9d1c6a0819083635b8246cc82e7 completed May 10, 2026, 6:09 p.m.
Created at: April 10, 2026, 5:30 a.m.