Triple
T3141767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–San Francisco |
E65663
|
entity |
| Predicate | typicalAircraftTypeCategory |
P45618
|
FINISHED |
| Object | wide-body jet |
—
|
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: wide-body jet | Statement: [Paris–San Francisco, typicalAircraftTypeCategory, wide-body jet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAircraftTypeCategory Context triple: [Paris–San Francisco, typicalAircraftTypeCategory, wide-body jet]
-
A.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
B.
commonAircraftFamily
Indicates that two aircraft belong to the same aircraft family or series, sharing a common design lineage.
-
C.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
-
D.
typicalAircraftStrength
Indicates the usual or characteristic level of military strength or capability associated with an aircraft.
-
E.
iataAircraftTypeCode
Indicates the standardized IATA code that specifies the aircraft type used in a flight or aviation 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_69ad8582f564819088c27e1f96153938 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada57895dc8190bd3d4ef9391973dc |
completed | March 8, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69ad9df840088190a26a1516f4c1f056 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:05 p.m.