Triple
T2603898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EXS |
E58609
|
entity |
| Predicate | codeUsage |
P2529
|
FINISHED |
| Object | airline identification in air traffic control |
—
|
LITERAL FINISHED |
How this triple was built (2 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: airline identification in air traffic control | Statement: [EXS, codeUsage, airline identification in air traffic control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeUsage Context triple: [EXS, codeUsage, airline identification in air traffic control]
-
A.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
B.
usageType
chosen
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
codeExample
Indicates that one entity provides a snippet or sample of source code that illustrates how to use, implement, or demonstrate another entity.
-
D.
code
Indicates that an entity writes, develops, or produces computer software or source code.
-
E.
codeFor
Indicates that one entity serves as the implementation, encoding, or programmatic representation for another entity.
- F. None of above.
Provenance (3 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.