Triple
T34845697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Metro 81-series trains |
E1004458
|
entity |
| Predicate | belongsToSeriesFamily |
P4276
|
FINISHED |
| Object | 81-series metro trains |
—
|
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: 81-series metro trains | Statement: [Moscow Metro 81-series trains, belongsToSeriesFamily, 81-series metro trains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToSeriesFamily Context triple: [Moscow Metro 81-series trains, belongsToSeriesFamily, 81-series metro trains]
-
A.
belongsToSeriesRange
Indicates that something is part of, or falls within, a specified series or sequence range.
-
B.
belongsToSeriesEntry
Indicates that something is an individual installment or component within a larger series or sequence.
-
C.
belongsToTypeSeries
Indicates that something is a member or instance of a particular type series or classification series.
-
D.
belongsToFamily
chosen
Indicates that an entity is a member of, or is associated as part of, a specific family group.
-
E.
belongsToSubseries
Indicates that one item is part of, or contained within, a more specific subseries of a larger series or collection.
- 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_69f76db97714819099b5bed36fd64e9d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff6a4ce9a08190b98abde3a170dd69 |
completed | May 9, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69ff69c11634819089d1084bd2c11534 |
completed | May 9, 2026, 5:07 p.m. |
Created at: May 3, 2026, 4 p.m.