Triple
T14295453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varadero Juan Gualberto Gómez Airport |
E354426
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
VRA
VRA is the IATA airport code for Varadero Juan Gualberto Gómez Airport, a major international gateway serving the resort city of Varadero in Cuba.
|
E1091725
|
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: VRA | Statement: [Varadero Juan Gualberto Gómez Airport, IATAcode, VRA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: VRA Context triple: [Varadero Juan Gualberto Gómez Airport, IATAcode, VRA]
-
A.
VRA
VRA is the common abbreviation for the landmark U.S. federal law enacted in 1965 to prohibit racial discrimination in voting.
-
B.
VRA
VRA is the regional public transport authority responsible for planning and coordinating mobility and infrastructure in the Amsterdam metropolitan area.
-
C.
VRR
VRR is a geologically distinct, hematite-rich ridge on Mars explored by NASA’s Curiosity rover as a key site for studying the planet’s past environmental conditions.
-
D.
VRR
VRR is the public transport association that coordinates and manages the integrated ticketing and fare system for much of the Rhine-Ruhr metropolitan region in Germany.
-
E.
VIR
VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
- 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: VRA Triple: [Varadero Juan Gualberto Gómez Airport, IATAcode, VRA]
Generated description
VRA is the IATA airport code for Varadero Juan Gualberto Gómez Airport, a major international gateway serving the resort city of Varadero in Cuba.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: VRA Target entity description: VRA is the IATA airport code for Varadero Juan Gualberto Gómez Airport, a major international gateway serving the resort city of Varadero in Cuba.
-
A.
VRA
VRA is the common abbreviation for the landmark U.S. federal law enacted in 1965 to prohibit racial discrimination in voting.
-
B.
VRA
VRA is the regional public transport authority responsible for planning and coordinating mobility and infrastructure in the Amsterdam metropolitan area.
-
C.
VRR
VRR is a geologically distinct, hematite-rich ridge on Mars explored by NASA’s Curiosity rover as a key site for studying the planet’s past environmental conditions.
-
D.
VRR
VRR is the public transport association that coordinates and manages the integrated ticketing and fare system for much of the Rhine-Ruhr metropolitan region in Germany.
-
E.
VIR
VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717b35ec81908968994e65737c66 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d246ccc81909e9fe8b4487dcc88 |
completed | May 8, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69fd3eabe838819099664221953ba756 |
completed | May 8, 2026, 1:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3f29b2148190931d415d6d5550a6 |
completed | May 8, 2026, 1:40 a.m. |
Created at: April 10, 2026, 1:11 a.m.