Triple
T7023760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colorado Springs Airport |
E162891
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
COS
COS is the IATA airport code for Colorado Springs Airport, a commercial airport serving Colorado Springs, Colorado, in the United States.
|
E636779
|
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: COS | Statement: [Colorado Springs Airport, IATAcode, COS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: COS Context triple: [Colorado Springs Airport, IATAcode, COS]
-
A.
COS
COS is the French Armed Forces' elite joint command responsible for planning and conducting special operations.
-
B.
COS
COS is the College of Science at Northeastern University, encompassing disciplines such as biology, chemistry, physics, mathematics, and related scientific fields.
-
C.
COS
COS is a Hubble Space Telescope instrument designed to study the origins and evolution of the universe by analyzing the ultraviolet light from distant astronomical objects.
-
D.
CLO
CLO is the acronym for the Conselh de la Lenga Occitana, the official body responsible for regulating and standardizing the Occitan language.
-
E.
KOS
KOS is the vehicle registration code assigned to the town of Oświęcim in southern Poland.
- 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: COS Triple: [Colorado Springs Airport, IATAcode, COS]
Generated description
COS is the IATA airport code for Colorado Springs Airport, a commercial airport serving Colorado Springs, Colorado, in the United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: COS Target entity description: COS is the IATA airport code for Colorado Springs Airport, a commercial airport serving Colorado Springs, Colorado, in the United States.
-
A.
COS
COS is a Hubble Space Telescope instrument designed to study the origins and evolution of the universe by analyzing the ultraviolet light from distant astronomical objects.
-
B.
COS
COS is the French Armed Forces' elite joint command responsible for planning and conducting special operations.
-
C.
COS
COS is the College of Science at Northeastern University, encompassing disciplines such as biology, chemistry, physics, mathematics, and related scientific fields.
-
D.
CLO
CLO is the acronym for the Conselh de la Lenga Occitana, the official body responsible for regulating and standardizing the Occitan language.
-
E.
KOS
KOS is the vehicle registration code assigned to the town of Oświęcim in southern Poland.
- 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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1fa043c81909c900e394a5972f9 |
completed | March 27, 2026, 8 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7757c87788190b09ced669b5c4d83 |
completed | March 28, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_69c7777be0d08190b6be22c72d2da12e |
completed | March 28, 2026, 6:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c77851ace48190a2a4899181f3d14a |
completed | March 28, 2026, 6:42 a.m. |
Created at: March 27, 2026, 2:35 p.m.