Triple
T4229287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 10L/28R |
E94537
|
entity |
| Predicate | hasRunwayDesignationSide |
P54806
|
FINISHED |
| Object | left for direction 10 |
—
|
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: left for direction 10 | Statement: [Runway 10L/28R, hasRunwayDesignationSide, left for direction 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayDesignationSide Context triple: [Runway 10L/28R, hasRunwayDesignationSide, left for direction 10]
-
A.
hasRunwaySide
Indicates that a runway is located on or associated with a particular side or boundary of another feature (such as an airport or airfield area).
-
B.
hasRunwayOrientation
Indicates that a runway is aligned or oriented in a specific directional heading.
-
C.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
D.
hasRunwayMarkings
Indicates that a runway possesses specific painted markings or symbols on its surface.
-
E.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
- F. None of above. chosen
Provenance (4 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e61ccc081909b880baf1d6a0f24 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f3bd188190b0cd613e8a5c1683 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:05 p.m.