Triple
T31729978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Augustine Airport |
E809833
|
entity |
| Predicate | runway2_20Orientation |
P6272
|
FINISHED |
| Object | 020/200 degrees |
—
|
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: 020/200 degrees | Statement: [St. Augustine Airport, runway2_20Orientation, 020/200 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway2_20Orientation Context triple: [St. Augustine Airport, runway2_20Orientation, 020/200 degrees]
-
A.
hasRunwayOrientation
chosen
Indicates that a runway is aligned or oriented in a specific directional heading.
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
runwayPair
Indicates that two runways are associated or grouped together as a functional pair, typically for coordinated or complementary use.
-
D.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
E.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 30, 2026, 11:21 p.m.