Triple
T1344230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lisbon Airport |
E28532
|
entity |
| Predicate | usesMetricRunway |
P27404
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Lisbon Airport, usesMetricRunway, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMetricRunway Context triple: [Lisbon Airport, usesMetricRunway, true]
-
A.
usesMetric
Indicates that one entity adopts, applies, or relies on a particular metric or measurement standard in its operation, evaluation, or description.
-
B.
hasRunwayLengthCategory
Indicates that an airport or airfield is associated with a specific categorical range of runway lengths (e.g., short, medium, long).
-
C.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
D.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
E.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23b8a9081908b78405d4ef806af |
completed | March 1, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69a4bef3e8fc8190ac9a1ba9b5879483 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c06721488190ac7f6e012f21af3d |
completed | March 1, 2026, 10:40 p.m. |
Created at: March 1, 2026, 7:56 p.m.