Triple
T15636998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | trolleybus line 21 (Gdynia–Sopot) |
E375970
|
entity |
| Predicate | languageOfRouteNumbering |
P87746
|
FINISHED |
| Object | Polish |
—
|
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: Polish | Statement: [trolleybus line 21 (Gdynia–Sopot), languageOfRouteNumbering, Polish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfRouteNumbering Context triple: [trolleybus line 21 (Gdynia–Sopot), languageOfRouteNumbering, Polish]
-
A.
languageOfRouteCountries
Indicates the languages used or officially spoken in the countries through which a given route passes.
-
B.
routeNumberFormat
Indicates how the identifying number or code for a route is structured or formatted.
-
C.
hasStreetNumberingSystem
Indicates that a location or area uses an organized system for assigning numbers to buildings or addresses along its streets.
-
D.
hasRoadNumberSystem
Indicates that a place or region uses a specific system for assigning numbers to its roads or highways.
-
E.
languageUsedOnRoute
chosen
Indicates that a particular language is used for communication (e.g., signage, announcements, or information) along a specific route.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eba51f08190ac5d9de7fc89405a |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:14 a.m.