Triple
T29595167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow trolleybus network |
E754272
|
entity |
| Predicate | peakRouteCount |
P29564
|
FINISHED |
| Object | over 80 routes |
—
|
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: over 80 routes | Statement: [Moscow trolleybus network, peakRouteCount, over 80 routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakRouteCount Context triple: [Moscow trolleybus network, peakRouteCount, over 80 routes]
-
A.
numberOfRoutes
chosen
Indicates the total count of distinct routes or paths associated with a given entity or between specified entities.
-
B.
popularRouteVia
Indicates that a route between two locations commonly or frequently passes through a specified intermediate point or path.
-
C.
tourLegCount
Indicates the number of legs or segments that make up a given tour or journey.
-
D.
totalRouteLength
Indicates the overall distance or length of an entire route when all its segments are combined.
-
E.
parentRouteNumber
Indicates that one route is the immediate higher-level or containing route from which another route is derived or subordinated.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66db7c2e08190a438ce9865666020 |
completed | May 2, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:17 p.m.