Triple
T32937157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grosse Ile Municipal Airport |
E842561
|
entity |
| Predicate | runway4R/22LLengthFeet |
P6291
|
FINISHED |
| Object | 4296 |
—
|
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: 4296 | Statement: [Grosse Ile Municipal Airport, runway4R/22LLengthFeet, 4296]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway4R/22LLengthFeet Context triple: [Grosse Ile Municipal Airport, runway4R/22LLengthFeet, 4296]
-
A.
runwayLength
chosen
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.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
D.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
E.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
- 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_69f34949727c81909d195c97de3341c8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: May 1, 2026, 1:20 a.m.