Triple
T892165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram |
E19262
|
entity |
| Predicate | notableModel |
P1503
|
FINISHED |
| Object | Ram ProMaster |
E97889
|
NE 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: Ram ProMaster | Statement: [Ram, notableModel, Ram ProMaster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ram ProMaster Context triple: [Ram, notableModel, Ram ProMaster]
-
A.
Ram ProMaster
chosen
The Ram ProMaster is a front-wheel-drive full-size commercial van known for its versatile cargo space, low load floor, and use in delivery, trades, and fleet applications.
-
B.
Ram 2500
The Ram 2500 is a heavy-duty full-size pickup truck known for its strong towing and hauling capabilities, offered by Ram Trucks for work and recreational use.
-
C.
GMC Savana
The GMC Savana is a full-size van produced by General Motors, commonly used for cargo transport, passenger shuttling, and commercial fleet applications.
-
D.
Ram 3500
The Ram 3500 is a heavy-duty full-size pickup truck known for its powerful towing and hauling capabilities, offered under the Ram Trucks brand.
-
E.
Ram Trucks
Ram Trucks is an American brand of light to heavy-duty pickup trucks and commercial vehicles known for its powerful performance and rugged design.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0304b081908d4c92bb2beadb81 |
completed | March 1, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c025464081908032939637248635 |
completed | March 4, 2026, 5:16 a.m. |
Created at: March 1, 2026, 7:39 p.m.