Triple
T10443491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Konstal 105Na |
E246225
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Konstal 105N2k |
E864114
|
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: Konstal 105N2k | Statement: [Konstal 105Na, hasVariant, Konstal 105N2k]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Konstal 105N2k Context triple: [Konstal 105Na, hasVariant, Konstal 105N2k]
-
A.
Konstal 105N
chosen
The Konstal 105N is a Polish high-floor tram model introduced in the 1970s, widely used in many cities across Poland as a standard single-section streetcar.
-
B.
Konstal 105Na tram
The Konstal 105Na tram is a widely used Polish high-floor tram model introduced in the late 20th century and operated in many cities across Poland.
-
C.
Konstal
Konstal is a Polish rolling stock manufacturer best known for producing trams and other urban rail vehicles used widely across Poland and Eastern Europe.
-
D.
Contrex
Contrex is a French mineral water brand known for its high mineral content and association with health and slimming.
-
E.
Rehau
Rehau is a small town in northeastern Bavaria, Germany, known historically for its textile and porcelain industries and today for its plastics manufacturing.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fdbd731c819084dfff83b4481ae8 |
completed | April 7, 2026, 12:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc43e53081909e14cfe295d17cb2 |
completed | April 10, 2026, 11:17 a.m. |
Created at: April 6, 2026, 12:15 p.m.