Triple
T20053306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ørland Airport |
E499259
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
OLA
OLA is the IATA airport code for Ørland Airport, a regional airport in Trøndelag county, Norway.
|
E1408868
|
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: OLA | Statement: [Ørland Airport, IATAcode, OLA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OLA Context triple: [Ørland Airport, IATAcode, OLA]
-
A.
OLA
OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
-
B.
OLA
OLA is a laser altimeter instrument on NASA’s OSIRIS-REx spacecraft used to create detailed 3D maps of the asteroid Bennu’s surface.
-
C.
OLE
OLE (Object Linking and Embedding) is a Microsoft technology that enables embedding and linking to documents and other objects within different applications, forming a foundation for later component technologies like ActiveX.
-
D.
OLE
OLE is the three-letter IATA airport code assigned to Cattaraugus County-Olean Airport in New York, United States.
-
E.
OL
OL is a UK postcode area covering Oldham and surrounding parts of Greater Manchester and nearby regions in North West England.
- 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: OLA Triple: [Ørland Airport, IATAcode, OLA]
Generated description
OLA is the IATA airport code for Ørland Airport, a regional airport in Trøndelag county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OLA Target entity description: OLA is the IATA airport code for Ørland Airport, a regional airport in Trøndelag county, Norway.
-
A.
OLA
OLA is the commonly used acronym for the United Nations Office of Legal Affairs, which provides legal advice and support to UN organs and specialized agencies.
-
B.
OLA
OLA is a laser altimeter instrument on NASA’s OSIRIS-REx spacecraft used to create detailed 3D maps of the asteroid Bennu’s surface.
-
C.
OLE
OLE is the three-letter IATA airport code assigned to Cattaraugus County-Olean Airport in New York, United States.
-
D.
OLE
OLE (Object Linking and Embedding) is a Microsoft technology that enables embedding and linking to documents and other objects within different applications, forming a foundation for later component technologies like ActiveX.
-
E.
OL
OL is a UK postcode area covering Oldham and surrounding parts of Greater Manchester and nearby regions in North West England.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6633043a481908359ad232607182a |
completed | April 20, 2026, 5:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08160a013c81908ef326ebb9140803 |
completed | May 16, 2026, 7 a.m. |
| NEDg | Description generation | batch_6a0816d3c71081909138d3144a108266 |
completed | May 16, 2026, 7:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a081798cb48819084ab456f79b68eb9 |
completed | May 16, 2026, 7:07 a.m. |
Created at: April 11, 2026, 3:38 p.m.