Triple
T1737837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Kosach family (Lesya Ukrainka’s family home) |
E37959
|
entity |
| Predicate | genreOfMuseum |
P7675
|
FINISHED |
| Object | biographical museum |
—
|
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: biographical museum | Statement: [House of Kosach family (Lesya Ukrainka’s family home), genreOfMuseum, biographical museum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfMuseum Context triple: [House of Kosach family (Lesya Ukrainka’s family home), genreOfMuseum, biographical museum]
-
A.
museumFocus
Indicates that a museum is primarily dedicated to or specializes in a particular subject, theme, or type of collection.
-
B.
museumSection
Indicates that one entity is a section, area, or subdivision within a museum associated with the other entity.
-
C.
majorMuseum
Indicates that a museum holds significant importance or prominence, typically due to its size, collections, reputation, or cultural impact.
-
D.
hasMuseumType
chosen
Indicates that an entity is classified as a museum of a specific type or category.
-
E.
museumAt
Indicates that an entity (such as an exhibit, artifact, or event) is located at or associated with a particular museum.
- 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_69a8861cc6ac8190ac0b2e31ccf62851 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab3c2559ac8190905186406fcaccb9 |
completed | March 6, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69aa61c4023c819099cbe439aefda71f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.