Triple
T33699273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SI-112 (Municipality of Sevnica) |
E863408
|
entity |
| Predicate | hasTerritorialUnitOfficialName |
P195195
|
FINISHED |
| Object | Municipality of Sevnica |
—
|
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: Municipality of Sevnica | Statement: [SI-112 (Municipality of Sevnica), hasTerritorialUnitOfficialName, Municipality of Sevnica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerritorialUnitOfficialName Context triple: [SI-112 (Municipality of Sevnica), hasTerritorialUnitOfficialName, Municipality of Sevnica]
-
A.
hasOfficialUNName
Indicates that an entity possesses an official name as formally recognized by the United Nations.
-
B.
hasOfficialNameInLatin
Indicates that an entity has an official or formally recognized name expressed in the Latin language.
-
C.
hasOfficialFrenchName
Indicates that an entity possesses an officially recognized name in the French language.
-
D.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
E.
hasOfficialLanguageOfToponym
Indicates that a toponym is associated with an official language in which that place name is formally recognized or used.
- F. None of above. chosen
Provenance (4 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdb04ed81c8190b8feea90c1c785a6 |
completed | May 8, 2026, 9:43 a.m. |
| PD | Predicate disambiguation | batch_69fda9d6c5148190a63205b6d9b0a1b4 |
completed | May 8, 2026, 9:16 a.m. |
| PDg | Predicate description generation | batch_69fdb04d37288190969a0f39d92efb49 |
completed | May 8, 2026, 9:43 a.m. |
Created at: May 1, 2026, 1:43 a.m.