Triple
T36750672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZL |
E907902
|
entity |
| Predicate | usedLanguageContext |
P8383
|
FINISHED |
| Object | Dutch rail context |
—
|
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: Dutch rail context | Statement: [ZL, usedLanguageContext, Dutch rail context]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguageContext Context triple: [ZL, usedLanguageContext, Dutch rail context]
-
A.
usesLanguageFor
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
B.
nativeLanguageContext
Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
-
C.
usesLanguageAs
Indicates that one entity communicates or operates using another entity as its language or linguistic medium.
-
D.
hasLanguageContext
chosen
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
E.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
- 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_69f76e76d10881909ec1679bc043108c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.