Triple
T4370488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram 2500 |
E98882
|
entity |
| Predicate | introducedAsRamBrand |
P5261
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Ram 2500, introducedAsRamBrand, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedAsRamBrand Context triple: [Ram 2500, introducedAsRamBrand, 2010]
-
A.
hasRAM
Indicates that an entity possesses or is equipped with a specified amount or type of random-access memory (RAM).
-
B.
chipsetBrand
Indicates the brand or manufacturer associated with a device’s chipset.
-
C.
maxRAMOfficial
Indicates the officially specified maximum amount of RAM that is supported or allowed for an entity (such as a device or system).
-
D.
hardwareRebrandingAssociatedWith
Indicates a relationship where one piece of hardware is linked to the rebranding or renaming of another hardware product or line.
-
E.
introducedAsBrandBy
chosen
Indicates that one entity was presented or launched to the public or a market as a brand by another entity.
- F. None of above.
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_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. |
Created at: March 12, 2026, 11:17 p.m.