Triple
T12341508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KAMAZ |
E294236
|
entity |
| Predicate | brandName |
P1500
|
FINISHED |
| Object | KAMAZ |
E294236
|
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: KAMAZ | Statement: [KAMAZ, brandName, KAMAZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KAMAZ Context triple: [KAMAZ, brandName, KAMAZ]
-
A.
KAMAZ
chosen
KAMAZ is a major Russian truck manufacturer known for producing heavy-duty vehicles and achieving multiple victories in the Dakar Rally.
-
B.
Omsktransmash
Omsktransmash is a major Russian tank and armored vehicle manufacturer based in Omsk, historically known for producing Soviet-era main battle tanks.
-
C.
GAZ (Gorky Automobile Plant)
GAZ (Gorky Automobile Plant) is a major Russian automotive manufacturer historically known for producing trucks, buses, and passenger cars, including many iconic Soviet-era vehicles.
-
D.
Traktor Chelyabinsk
Traktor Chelyabinsk is a professional ice hockey club from Chelyabinsk, Russia, historically recognized as one of the prominent teams in Soviet and Russian hockey.
-
E.
Avtovo
Avtovo is a renowned Saint Petersburg Metro station celebrated for its ornate, palace-like interior and distinctive Soviet-era architectural 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7758dc8190bbc6a9ad00b01dce |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aaa1d548190be065412aab70385 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.