Triple
T34934683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smiley Creek, Idaho |
E1007532
|
entity |
| Predicate | airstripUse |
P182887
|
FINISHED |
| Object | seasonal |
—
|
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: seasonal | Statement: [Smiley Creek, Idaho, airstripUse, seasonal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airstripUse Context triple: [Smiley Creek, Idaho, airstripUse, seasonal]
-
A.
runwayUsedAs
Indicates that a particular runway is being utilized for a specific purpose, role, or operational function.
-
B.
hasEmergencyAirstrip
Indicates that an entity possesses or includes an airstrip specifically designated and equipped for emergency use.
-
C.
airfieldUsedDuring
Indicates that an airfield was in operational use during a specified time period or event.
-
D.
hasRunwayUse
Indicates that a particular runway is authorized or designated for use by a specific aircraft, operation, or purpose.
-
E.
airfieldRole
Indicates the functional role or operational purpose that an airfield serves within a broader system or context.
- 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_69f76dc513fc819084a1ff52abbfa5bc |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4 p.m.