Triple
T8771122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 71-619 |
E208462
|
entity |
| Predicate | hasUsageLevel |
P85306
|
FINISHED |
| Object | widely used tram model in Russia |
—
|
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: widely used tram model in Russia | Statement: [71-619, hasUsageLevel, widely used tram model in Russia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUsageLevel Context triple: [71-619, hasUsageLevel, widely used tram model in Russia]
-
A.
hasLevel
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
B.
hasUsageNote
Indicates that there is an associated explanatory note describing how or when something should be used.
-
C.
hasLevelType
Indicates that an entity is associated with a specific type or category of level (e.g., difficulty, hierarchy, or stage).
-
D.
hasHistoricalUsageIn
Indicates that something has been used or practiced within a particular historical period, context, or tradition.
-
E.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
- F. None of above. chosen
Provenance (4 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2b08f881909f3d4fab2eda1d67 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.