Triple
T10781453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casey |
E254326
|
entity |
| Predicate | hasLogisticsSupport |
P28699
|
FINISHED |
| Object | ice runway at Wilkins Aerodrome |
—
|
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: ice runway at Wilkins Aerodrome | Statement: [Casey, hasLogisticsSupport, ice runway at Wilkins Aerodrome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLogisticsSupport Context triple: [Casey, hasLogisticsSupport, ice runway at Wilkins Aerodrome]
-
A.
logisticsSupportFrom
Indicates that one entity provides logistical assistance, resources, or services to another entity.
-
B.
logisticsFeature
chosen
Indicates that something possesses a characteristic, capability, or function specifically related to logistics operations or processes.
-
C.
hasCargoServices
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
-
D.
hasSupportService
Indicates that one entity provides or is associated with a support-related service for another entity.
-
E.
hasFreightFacility
Indicates that an entity is equipped with or connected to a facility used for handling, loading, unloading, or storing freight.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732c48c488190a2b3162202b74726 |
completed | April 9, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69d6f31455648190b5c24690487b1b54 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.