Triple
T29260847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balcarres House alterations, Fife |
E741839
|
entity |
| Predicate | languageOfDesignDrawings |
P81678
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Balcarres House alterations, Fife, languageOfDesignDrawings, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfDesignDrawings Context triple: [Balcarres House alterations, Fife, languageOfDesignDrawings, English]
-
A.
legalDesignationLanguage
Indicates the language in which a legal designation, status, or title is formally expressed or recorded.
-
B.
primaryLanguageOfDesignTradition
chosen
Indicates the main natural language used within a particular design tradition for its communication, documentation, and conceptual development.
-
C.
languageUsedInDepiction
Indicates that a particular language is used within a depiction, such as in its text, dialogue, or other linguistic content.
-
D.
languageDesigned
Indicates that one entity created or developed the language used or associated with another entity.
-
E.
hasDesignLanguage
Indicates that one entity employs, follows, or is characterized by the design language specified by 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_69f0912065c08190bddd23e20e8ef18e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: April 28, 2026, 12:41 p.m.