Triple

T13664947
Position Surface form Disambiguated ID Type / Status
Subject Rutland–Southern Vermont Regional Airport E327092 entity
Predicate FAAIdentifier P420 FINISHED
Object RUT
RUT is the FAA airport code for Rutland–Southern Vermont Regional Airport, a public airport serving the Rutland region of Vermont.
 E1055050 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: RUT | Statement: [Rutland–Southern Vermont Regional Airport, FAAIdentifier, RUT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RUT
Context triple: [Rutland–Southern Vermont Regional Airport, FAAIdentifier, RUT]
  • A. RUT
    RUT is the ticker symbol for the Russell 2000 Index, a major U.S. stock market index tracking the performance of approximately 2,000 small-cap companies.
  • B. RUD
    RUD is the Amtrak station code for the Rutland train station in Rutland, Vermont, used for ticketing and scheduling on the U.S. passenger rail network.
  • C. RÜG
    RÜG is the vehicle registration code used for motor vehicles registered in the district of Vorpommern-Rügen in the German state of Mecklenburg-Vorpommern.
  • D. RÜD
    RÜD is the German vehicle registration code for the Rheingau-Taunus-Kreis district in the state of Hesse.
  • E. RUG
    RUG is the commonly used abbreviation for the University of Groningen, a major public research university in the Netherlands.
  • 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: RUT
Triple: [Rutland–Southern Vermont Regional Airport, FAAIdentifier, RUT]
Generated description
RUT is the FAA airport code for Rutland–Southern Vermont Regional Airport, a public airport serving the Rutland region of Vermont.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RUT
Target entity description: RUT is the FAA airport code for Rutland–Southern Vermont Regional Airport, a public airport serving the Rutland region of Vermont.
  • A. RUT
    RUT is the ticker symbol for the Russell 2000 Index, a major U.S. stock market index tracking the performance of approximately 2,000 small-cap companies.
  • B. RUD
    RUD is the Amtrak station code for the Rutland train station in Rutland, Vermont, used for ticketing and scheduling on the U.S. passenger rail network.
  • C. RÜG
    RÜG is the vehicle registration code used for motor vehicles registered in the district of Vorpommern-Rügen in the German state of Mecklenburg-Vorpommern.
  • D. RÜD
    RÜD is the German vehicle registration code for the Rheingau-Taunus-Kreis district in the state of Hesse.
  • E. RUG
    RUG is the commonly used abbreviation for the University of Groningen, a major public research university in the Netherlands.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc622a07c81909ef7fb55e719dd9a completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7943bfaf0819097410e901847d77c completed May 3, 2026, 6:30 p.m.
NEDg Description generation batch_69f79655d5f08190a3cbf3e12e2ffa67 completed May 3, 2026, 6:39 p.m.
NED2 Entity disambiguation (via description) batch_69f7972a1cf48190a1d435227414967a completed May 3, 2026, 6:42 p.m.
Created at: April 9, 2026, 9:52 p.m.