Triple
T7217953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toyota RAV4 |
E150182
|
entity |
| Predicate | salesCharacteristic |
P75508
|
FINISHED |
| Object | one of Toyota’s best-selling models worldwide |
—
|
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: one of Toyota’s best-selling models worldwide | Statement: [Toyota RAV4, salesCharacteristic, one of Toyota’s best-selling models worldwide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: salesCharacteristic Context triple: [Toyota RAV4, salesCharacteristic, one of Toyota’s best-selling models worldwide]
-
A.
pricingCharacteristic
Indicates how the price of something is determined, structured, or behaves (e.g., fixed, variable, discounted, tiered).
-
B.
catalogCharacteristic
Indicates that a catalog has a specific characteristic or attribute associated with it.
-
C.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
-
D.
projectCharacteristics
Indicates the defining features, qualities, or attributes that characterize a particular project.
-
E.
campaignCharacteristics
Indicates the defining features, attributes, or qualities that characterize a particular campaign.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e99170d88190b1aef326a7d81134 |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e889854481908c765ce2107f2d3a |
completed | March 27, 2026, 8:28 p.m. |
Created at: March 27, 2026, 2:53 p.m.