Triple
T6826344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binter Canarias |
E157024
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object |
BINTER
BINTER is the airline callsign used by Binter Canarias, a Spanish regional carrier primarily serving the Canary Islands and nearby destinations.
|
E621641
|
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: BINTER | Statement: [Binter Canarias, callsign, BINTER]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BINTER Context triple: [Binter Canarias, callsign, BINTER]
-
A.
BIE
BIE is a U.S. federal agency within the Department of the Interior responsible for providing and overseeing education services for Native American students in schools on or near reservations.
-
B.
BIE
BIE is the commonly used acronym for the Bureau International des Expositions, the intergovernmental organization that oversees and regulates World Expos.
-
C.
BIF
BIF is the National Rail station code for Barrow-in-Furness railway station in Cumbria, England.
-
D.
BIAP
BIAP is the commonly used acronym for Baghdad International Airport, the main international airport serving Baghdad, Iraq.
-
E.
BIFA
BIFA is the organization that runs the British Independent Film Awards, celebrating excellence in independent filmmaking in the United Kingdom.
- 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: BINTER Triple: [Binter Canarias, callsign, BINTER]
Generated description
BINTER is the airline callsign used by Binter Canarias, a Spanish regional carrier primarily serving the Canary Islands and nearby destinations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BINTER Target entity description: BINTER is the airline callsign used by Binter Canarias, a Spanish regional carrier primarily serving the Canary Islands and nearby destinations.
-
A.
BIE
BIE is a U.S. federal agency within the Department of the Interior responsible for providing and overseeing education services for Native American students in schools on or near reservations.
-
B.
BIE
BIE is the commonly used acronym for the Bureau International des Expositions, the intergovernmental organization that oversees and regulates World Expos.
-
C.
BIF
BIF is the National Rail station code for Barrow-in-Furness railway station in Cumbria, England.
-
D.
BIAP
BIAP is the commonly used acronym for Baghdad International Airport, the main international airport serving Baghdad, Iraq.
-
E.
BIFA
BIFA is the organization that runs the British Independent Film Awards, celebrating excellence in independent filmmaking in the United Kingdom.
- 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_69c6882a5b5c8190917a7db9ed36bad1 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d58375248190935dd38d618994e3 |
completed | March 27, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723f12a148190adbb05782a2041b6 |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c7251ec97c819094fb2a73ac1d1d0e |
completed | March 28, 2026, 12:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c725d04d988190a4a6a1c73056cfd7 |
completed | March 28, 2026, 12:50 a.m. |
Created at: March 27, 2026, 2:18 p.m.