Triple
T20926426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellington-de-l’Église |
E515355
|
entity |
| Predicate | roadNetworkLanguage |
P127216
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Wellington-de-l’Église, roadNetworkLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadNetworkLanguage Context triple: [Wellington-de-l’Église, roadNetworkLanguage, French]
-
A.
hasStreetNameLanguage
chosen
Indicates that the language in which a street name is expressed is specified.
-
B.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
C.
roadNetworkJurisdiction
Indicates the authority or entity responsible for managing, regulating, or maintaining a given segment of the road network.
-
D.
languageRegionsAlongRoute
Indicates the languages spoken in the geographic regions that lie along a specified route.
-
E.
roadNetworkContext
Indicates the contextual relationship between elements within a road network, such as how roads, intersections, and related infrastructure are organized or interact.
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f65200b08190ac208204a20f5a6a |
completed | April 21, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e5c9af1fe08190953366a466950140 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:49 p.m.