Triple

T22774575
Position Surface form Disambiguated ID Type / Status
Subject São Tomé International Airport E563658 entity
Predicate IATAcode P418 FINISHED
Object TMS
TMS is the IATA airport code for São Tomé International Airport, the main air gateway to the island nation of São Tomé and Príncipe.
 E1553654 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: TMS | Statement: [São Tomé International Airport, IATAcode, TMS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TMS
Context triple: [São Tomé International Airport, IATAcode, TMS]
  • A. TMS
    TMS (Test Mode Select) is the JTAG control signal used to navigate the TAP (Test Access Port) state machine in IEEE 1149.1 boundary-scan operations.
  • B. TMS
    TMS is a British songwriting and production team known for crafting pop and contemporary hits for major artists.
  • C. TMB
    TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
  • D. TMB
    TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
  • E. TAM
    TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
  • 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: TMS
Triple: [São Tomé International Airport, IATAcode, TMS]
Generated description
TMS is the IATA airport code for São Tomé International Airport, the main air gateway to the island nation of São Tomé and Príncipe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TMS
Target entity description: TMS is the IATA airport code for São Tomé International Airport, the main air gateway to the island nation of São Tomé and Príncipe.
  • A. TMS
    TMS (Test Mode Select) is the JTAG control signal used to navigate the TAP (Test Access Port) state machine in IEEE 1149.1 boundary-scan operations.
  • B. TMS
    TMS is a British songwriting and production team known for crafting pop and contemporary hits for major artists.
  • C. TMB
    TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
  • D. TMB
    TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
  • E. TAM
    TAM is a prominent annual conference focused on science, skepticism, and critical thinking, originally organized by the James Randi Educational Foundation.
  • 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_69e24554497c819080b996e071de27c2 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17b60eec48190b0aaf3eb7ede38d4 completed April 29, 2026, 3:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b9824f4108190b430ea2138a57ba0 completed May 18, 2026, 10:52 p.m.
NEDg Description generation batch_6a0b9970f0388190a71f234f8022fc3e completed May 18, 2026, 10:57 p.m.
NED2 Entity disambiguation (via description) batch_6a0b9a1129c8819084163353accc7e14 completed May 18, 2026, 11 p.m.
Created at: April 17, 2026, 3:27 p.m.