Triple
T1363094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gran Canaria Airport |
E29139
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object |
Gando Airport
Gando Airport is the main international airport serving Gran Canaria in Spain’s Canary Islands.
|
E157271
|
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: Gando Airport | Statement: [Gran Canaria Airport, alternativeName, Gando Airport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gando Airport Context triple: [Gran Canaria Airport, alternativeName, Gando Airport]
-
A.
Tajima Airport
Tajima Airport is a regional airport in northern Hyogo Prefecture, Japan, primarily serving domestic flights and connecting the Tajima area with major Japanese cities.
-
B.
Hana Airport
Hana Airport is a small regional airport serving the remote town of Hāna on the eastern coast of Maui, Hawaii.
-
C.
Dabolim Airport
Dabolim Airport is the main international airport serving the Indian state of Goa, handling both civilian and military air traffic.
-
D.
Panguilemo Airport
Panguilemo Airport is a regional public airport serving the city of Talca and the surrounding Maule Region in central Chile.
-
E.
Naha Airport
Naha Airport is the main commercial airport serving Okinawa Prefecture in Japan, acting as a key domestic and regional hub in the Ryukyu Islands.
- 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: Gando Airport Triple: [Gran Canaria Airport, alternativeName, Gando Airport]
Generated description
Gando Airport is the main international airport serving Gran Canaria in Spain’s Canary Islands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gando Airport Target entity description: Gando Airport is the main international airport serving Gran Canaria in Spain’s Canary Islands.
-
A.
Tajima Airport
Tajima Airport is a regional airport in northern Hyogo Prefecture, Japan, primarily serving domestic flights and connecting the Tajima area with major Japanese cities.
-
B.
Hana Airport
Hana Airport is a small regional airport serving the remote town of Hāna on the eastern coast of Maui, Hawaii.
-
C.
Dabolim Airport
Dabolim Airport is the main international airport serving the Indian state of Goa, handling both civilian and military air traffic.
-
D.
Panguilemo Airport
Panguilemo Airport is a regional public airport serving the city of Talca and the surrounding Maule Region in central Chile.
-
E.
Naha Airport
Naha Airport is the main commercial airport serving Okinawa Prefecture in Japan, acting as a key domestic and regional hub in the Ryukyu Islands.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c2b4ab3c8190ad692e32eee05976 |
completed | March 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acd47d38388190856b4ae9de1e69d7 |
completed | March 8, 2026, 1:44 a.m. |
| NEDg | Description generation | batch_69acd543a0ac8190b9fd5e921b5ad9ea |
completed | March 8, 2026, 1:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acd5b8fa2481908fd52d94e55b6377 |
completed | March 8, 2026, 1:49 a.m. |
Created at: March 1, 2026, 7:57 p.m.