Triple
T12561669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Assembly building, Sofia |
E295365
|
entity |
| Predicate | hasFacadeInscriptionTranslation |
P5528
|
FINISHED |
| Object | “Unity makes strength” |
—
|
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: “Unity makes strength” | Statement: [National Assembly building, Sofia, hasFacadeInscriptionTranslation, “Unity makes strength”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacadeInscriptionTranslation Context triple: [National Assembly building, Sofia, hasFacadeInscriptionTranslation, “Unity makes strength”]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasInscriptions
Indicates that an object, surface, or artifact bears written, carved, or engraved inscriptions on it.
-
C.
inscriptionTranslation
chosen
Indicates that a provided text expresses the translated content of a specific inscription.
-
D.
hasTranslationNote
Indicates that there is an explanatory note about how something has been translated, such as clarifying wording choices, alternatives, or translation issues.
-
E.
hasTranslationPlatform
Indicates that one entity provides or is associated with a platform used to perform or manage translations for another entity.
- 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.