Triple
T12561668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Assembly building, Sofia |
E295365
|
entity |
| Predicate | hasFacadeInscriptionLanguage |
P9278
|
FINISHED |
| Object | Bulgarian |
—
|
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: Bulgarian | Statement: [National Assembly building, Sofia, hasFacadeInscriptionLanguage, Bulgarian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacadeInscriptionLanguage Context triple: [National Assembly building, Sofia, hasFacadeInscriptionLanguage, Bulgarian]
-
A.
hasLanguageOn
chosen
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
B.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
C.
hasLanguageStatus
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
D.
hasOfficerLanguage
Indicates that an officer is able or authorized to communicate in a specified language.
-
E.
hasLanguageGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9550d84908190aea0f50055f6d92e |
completed | April 10, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69d95414692881909c52a1de7d224b44 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 11:48 p.m.