Triple
T13634415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tupolev Tu-334 |
E325809
|
entity |
| Predicate | rangeWithFullPayload_km |
P111389
|
FINISHED |
| Object | 3150 |
—
|
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: 3150 | Statement: [Tupolev Tu-334, rangeWithFullPayload_km, 3150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rangeWithFullPayload_km Context triple: [Tupolev Tu-334, rangeWithFullPayload_km, 3150]
-
A.
range_km
Indicates the maximum distance, measured in kilometers, over which something can operate, travel, or be effective.
-
B.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
C.
lengthInKm
Indicates that one entity specifies the length or distance of another entity measured in kilometers.
-
D.
rangeWithFullPassengers_nm
Indicates the maximum distance an entity (such as a vehicle or vessel) can travel when carrying its full complement of passengers, measured in nautical miles.
-
E.
dimensions_km
Indicates the physical size or extent of something measured in kilometers, typically specifying one or more linear dimensions (e.g., length, width, height).
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe85e1c4819095194f4b7f9f6118 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc6043e148190a2a25f929cfa35e5 |
completed | April 12, 2026, 4:19 p.m. |
Created at: April 9, 2026, 9:51 p.m.