Triple
T23525626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Sebastián Airport |
E576423
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
LESO
LESO is the ICAO airport code for San Sebastián Airport, a regional airport serving the city of San Sebastián in northern Spain.
|
E1591267
|
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: LESO | Statement: [San Sebastián Airport, ICAOcode, LESO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LESO Context triple: [San Sebastián Airport, ICAOcode, LESO]
-
A.
LEISA
LEISA is the infrared imaging spectrometer subsystem of New Horizons’ Ralph instrument, used to map the composition and temperature of planetary surfaces and atmospheres.
-
B.
L.E.S.
L.E.S. is an American hip-hop producer best known for his work with Nas and other prominent East Coast rap artists in the 1990s and 2000s.
-
C.
Lesse
The Lesse is a scenic river in southern Belgium known for flowing through the Ardennes, its limestone caves, and popular kayaking routes.
-
D.
LEST
LEST is the ICAO airport code for Santiago–Rosalía de Castro Airport in Santiago de Compostela, Spain.
-
E.
Leshiy
Leshiy is a forest spirit from Slavic mythology that was used as the official mascot for the 2013 World Championships in Athletics in Moscow.
- 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: LESO Triple: [San Sebastián Airport, ICAOcode, LESO]
Generated description
LESO is the ICAO airport code for San Sebastián Airport, a regional airport serving the city of San Sebastián in northern Spain.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LESO Target entity description: LESO is the ICAO airport code for San Sebastián Airport, a regional airport serving the city of San Sebastián in northern Spain.
-
A.
LEISA
LEISA is the infrared imaging spectrometer subsystem of New Horizons’ Ralph instrument, used to map the composition and temperature of planetary surfaces and atmospheres.
-
B.
L.E.S.
L.E.S. is an American hip-hop producer best known for his work with Nas and other prominent East Coast rap artists in the 1990s and 2000s.
-
C.
Lesse
The Lesse is a scenic river in southern Belgium known for flowing through the Ardennes, its limestone caves, and popular kayaking routes.
-
D.
LEST
LEST is the ICAO airport code for Santiago–Rosalía de Castro Airport in Santiago de Compostela, Spain.
-
E.
Leshiy
Leshiy is a forest spirit from Slavic mythology that was used as the official mascot for the 2013 World Championships in Athletics in Moscow.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac73be64819083e4a1c2c09551fb |
completed | April 29, 2026, 7 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0cdf51c4b88190bece408e0c4e06b5 |
completed | May 19, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_6a0ce22245488190acf1f8e40f23815c |
completed | May 19, 2026, 10:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ce27b51cc81908d1ffe2a76c23386 |
completed | May 19, 2026, 10:21 p.m. |
Created at: April 17, 2026, 6:09 p.m.