Triple
T2660528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IOSA |
E54714
|
entity |
| Predicate | evaluationArea |
P18032
|
FINISHED |
| Object | flight operations |
—
|
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: flight operations | Statement: [IOSA, evaluationArea, flight operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evaluationArea Context triple: [IOSA, evaluationArea, flight operations]
-
A.
assessmentAreaDefinedBy
chosen
Indicates that the scope or domain of an assessment is specified or delimited by a particular area or boundary.
-
B.
evaluationBasis
Indicates the criteria, standards, or reference framework used to judge, assess, or measure something in an evaluation process.
-
C.
engagementArea
Indicates the spatial region or scope within which an entity’s actions, influence, or interactions are intended to occur.
-
D.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
E.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd9504d10819091abc03532a2fa6d |
completed | March 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.