Triple
T25771227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghibli Museum |
E649024
|
entity |
| Predicate | languageOfSupportMaterials |
P180691
|
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: [Ghibli Museum, languageOfSupportMaterials, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfSupportMaterials Context triple: [Ghibli Museum, languageOfSupportMaterials, English]
-
A.
languageOfMaterial
Indicates the language in which a given material, resource, or content is expressed or presented.
-
B.
languageOfDocumentation
Indicates the language in which the documentation for an entity is written or provided.
-
C.
languageOfProvision
Indicates the language in which a provision, such as a legal or contractual clause, is written or officially expressed.
-
D.
languageOfProduct
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
-
E.
languageOfCoverage
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
- 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_69e7ab333b508190b6d708d8d9a328ed |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
| PDg | Predicate description generation | batch_69f74c6fa6548190b03935f65429a24e |
completed | May 3, 2026, 1:23 p.m. |
Created at: April 22, 2026, 5:29 a.m.