Triple
T24801322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gladiator Mojave |
E620529
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object |
Chevrolet Colorado off-road trims
Chevrolet Colorado off-road trims are specialized versions of the midsize Colorado pickup designed for enhanced trail capability, rugged performance, and off-road-focused features.
|
E1651862
|
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: Chevrolet Colorado off-road trims | Statement: [Gladiator Mojave, competesWith, Chevrolet Colorado off-road trims]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Chevrolet Colorado off-road trims Triple: [Gladiator Mojave, competesWith, Chevrolet Colorado off-road trims]
Generated description
Chevrolet Colorado off-road trims are specialized versions of the midsize Colorado pickup designed for enhanced trail capability, rugged performance, and off-road-focused features.
Provenance (5 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f412aacd388190aa3cae919d6bdee2 |
completed | May 1, 2026, 2:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a101c33902481909371cfe73e2d6eaf |
completed | May 22, 2026, 9:04 a.m. |
| NEDg | Description generation | batch_6a1025b941fc819081957c8e7d21b7f1 |
completed | May 22, 2026, 9:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a10265a02e08190b628804a79f31882 |
completed | May 22, 2026, 9:48 a.m. |
Created at: April 18, 2026, 4:49 a.m.