Triple
T17180799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honda CBR1100XX |
E416975
|
entity |
| Predicate | wetWeight |
P126640
|
FINISHED |
| Object | approximately 254 kg |
—
|
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: approximately 254 kg | Statement: [Honda CBR1100XX, wetWeight, approximately 254 kg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wetWeight Context triple: [Honda CBR1100XX, wetWeight, approximately 254 kg]
-
A.
emptyWeight
Indicates the weight of an object or vehicle when it is empty, excluding any load, cargo, or passengers.
-
B.
وزن
Indicates a relationship where one entity has, measures, or is characterized by a certain weight or mass.
-
C.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
D.
deadweightTonnage
Indicates the total carrying capacity of a vessel, measured as the maximum weight of cargo, fuel, passengers, provisions, and other loads it can safely transport.
-
E.
approximateWeightInPounds
Indicates the estimated weight of an entity expressed in pounds, rather than an exact measured value.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc1187808190aeaa0d0e6487957e |
completed | April 18, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e39c2fedb881908bfed2c3e5f2616a |
completed | April 18, 2026, 2:58 p.m. |
Created at: April 10, 2026, 5:37 a.m.