Triple
T4370495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram 2500 |
E98882
|
entity |
| Predicate | offersTrimLevel |
P55815
|
FINISHED |
| Object | Tradesman |
—
|
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: Tradesman | Statement: [Ram 2500, offersTrimLevel, Tradesman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersTrimLevel Context triple: [Ram 2500, offersTrimLevel, Tradesman]
-
A.
offersGrade
Indicates that one entity assigns or provides an academic grade or evaluation to another entity.
-
B.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
-
C.
offersEdition
Indicates that one entity provides or makes available a particular version or edition of another entity.
-
D.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
E.
offersPass
Indicates that one entity provides or makes available a pass (such as a ticket, permit, or access credential) to another entity.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3521cb7ec8190b7b79675871d97d8 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:17 p.m.