Triple
T7946132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enshi Xujiaping Airport |
E184501
|
entity |
| Predicate | runwayLengthUnit |
P79966
|
FINISHED |
| Object | meters |
—
|
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: meters | Statement: [Enshi Xujiaping Airport, runwayLengthUnit, meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayLengthUnit Context triple: [Enshi Xujiaping Airport, runwayLengthUnit, meters]
-
A.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
B.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
C.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
D.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
-
E.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
- 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b29a570819091a2ac185a8d57c4 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf788db1c8190839523e7777961d6 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:09 p.m.