Triple
T20301591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Södertälje derby |
E505492
|
entity |
| Predicate | languageOfLocalCoverage |
P38135
|
FINISHED |
| Object | Swedish |
—
|
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: Swedish | Statement: [Södertälje derby, languageOfLocalCoverage, Swedish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalCoverage Context triple: [Södertälje derby, languageOfLocalCoverage, Swedish]
-
A.
languageOfCoverage
chosen
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
B.
languageFamilyCoverage
Indicates the extent to which a given entity (such as a resource, model, or system) supports or covers the languages within a specified language family.
-
C.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
-
D.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
E.
languageOfLocalOrganization
Indicates the language used or officially adopted by a local organization in its operations or communications.
- 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_69e0b4b8ab648190906e18538c250148 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6770d82b48190b21ce7c52ec6d5a0 |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:17 a.m.