Triple
T9035580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 16L/34R |
E216483
|
entity |
| Predicate | hasRunwayNumberSuffix |
P54806
|
FINISHED |
| Object | L |
—
|
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: L | Statement: [Runway 16L/34R, hasRunwayNumberSuffix, L]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunwayNumberSuffix Context triple: [Runway 16L/34R, hasRunwayNumberSuffix, L]
-
A.
hasRunwayNumber
Indicates that an airport or airfield runway is assigned a specific identifying number.
-
B.
usesRunwayNumberingConvention
Indicates that an airport or runway follows a specific standardized system for assigning runway identification numbers.
-
C.
hasRunwayCount
Indicates the number of runways that a given entity (such as an airport) possesses.
-
D.
hasRunwayDesignationSide
chosen
Indicates that a runway designation is associated with a specific side or direction of the runway (e.g., left, right, or center).
-
E.
hasRunwayType
Indicates that an airport or airfield has a runway of a specified type or surface classification.
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6ac0b00c8190a7250b86bb7cc276 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.