Triple
T31363168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | road I/38 |
E799934
|
entity |
| Predicate | connectsCountryRegion |
P99274
|
FINISHED |
| Object | Central Bohemian Region |
—
|
NE NERFINISHED |
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: Central Bohemian Region | Statement: [road I/38, connectsCountryRegion, Central Bohemian Region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsCountryRegion Context triple: [road I/38, connectsCountryRegion, Central Bohemian Region]
-
A.
connectsCountryOrRegion
chosen
Indicates that one entity establishes a connection, link, or association to a specific country or region.
-
B.
connectsProvinceOrRegion
Indicates that one entity serves to link or provide a connection between a specific province or region and another entity.
-
C.
connectsCountryDirection
Indicates that one country is geographically connected to another in a specified cardinal or relative direction (e.g., north, south, east, west).
-
D.
connectsPortRegion
Indicates that one entity serves as a linkage or interface between a specific port and a defined region.
-
E.
connectsRegionalCity
Indicates a relationship where one entity serves as a link or transport route between a regional city and another location.
- 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_69f224e6b7448190ac6bf97ad7364160 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe96c2647c819082989f11e1ae3d35 |
completed | May 9, 2026, 2:06 a.m. |
| PD | Predicate disambiguation | batch_69fe928615448190af939e5a94be55bb |
completed | May 9, 2026, 1:48 a.m. |
Created at: April 29, 2026, 9:18 p.m.