Triple
T35429864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTM |
E1024025
|
entity |
| Predicate | runwayMetricUsed |
P27404
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [CTM, runwayMetricUsed, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayMetricUsed Context triple: [CTM, runwayMetricUsed, yes]
-
A.
usesMetricRunway
chosen
Indicates that a runway is measured, marked, or operated using metric units rather than imperial units.
-
B.
runwayUsedAs
Indicates that a particular runway is being utilized for a specific purpose, role, or operational function.
-
C.
runwayUsage
Indicates that a particular runway is being used or assigned for aircraft operations such as takeoffs or landings.
-
D.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
E.
runwayPerformance
Indicates the performance characteristics or behavior of an entity (such as an aircraft or vehicle) when operating on a runway, including factors like acceleration, deceleration, and required distances.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:03 p.m.