Triple
T21714452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summit Airport |
E535986
|
entity |
| Predicate | has tie-downs |
P49166
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Summit Airport, has tie-downs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has tie-downs Context triple: [Summit Airport, has tie-downs, yes]
-
A.
hasTieDowns
chosen
Indicates that an object, structure, or vehicle is equipped with tie-down points or devices for securing loads or attachments.
-
B.
harnesses
Indicates that one entity effectively utilizes, controls, or channels the power, resources, or capabilities of another for a particular purpose.
-
C.
hasArrestingGear
Indicates that an entity is equipped with a system or mechanism used to rapidly decelerate and stop another entity, typically during landing or capture.
-
D.
towingCapability
Indicates the maximum load or object weight that one entity is able to pull or tow.
-
E.
usesTwoLeggedTies
Indicates that one entity employs or applies two-legged ties in relation to another entity 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_69e0c46c6dd88190a595375fa6ebd701 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb5369be88190bafc10863d4d1bd7 |
completed | April 27, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:47 p.m.