Triple
T38377838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Дворцовый мост |
E893673
|
entity |
| Predicate | количествоРазводныхПролётов |
P190910
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Дворцовый мост, количествоРазводныхПролётов, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: количествоРазводныхПролётов Context triple: [Дворцовый мост, количествоРазводныхПролётов, 1]
-
A.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
-
B.
quantityFlown
Indicates the amount or volume that has been transported by flying from one place to another.
-
C.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
-
D.
flownOver
Indicates that one entity has moved through the air above or across another entity or location.
-
E.
numberOfRunways
Indicates the quantity of runways associated with a given entity, such as an airport or airfield.
- 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_69f76e4b1f748190a380696a16eae4a2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd34596288190b8e34a7a20b4c0db |
completed | May 7, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd31227708190a7df213597e66ca8 |
completed | May 7, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:31 p.m.