Triple
T36906396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finlandia |
E912788
|
entity |
| Predicate | hasSectionUsedAs |
P180951
|
FINISHED |
| Object | Christian hymn tune |
—
|
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: Christian hymn tune | Statement: [Finlandia, hasSectionUsedAs, Christian hymn tune]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSectionUsedAs Context triple: [Finlandia, hasSectionUsedAs, Christian hymn tune]
-
A.
hasSectionIn
Indicates that one entity contains or includes another entity as a section or subdivision within it.
-
B.
hasSectionOn
Indicates that one entity (typically a document or resource) contains a dedicated section or part that specifically addresses or discusses another entity or topic.
-
C.
hasSectionWith
Indicates that an entity contains or includes a specific section that satisfies certain conditions or characteristics.
-
D.
usesSectionOf
chosen
Indicates that one entity makes use of a specific section or part of another entity.
-
E.
hasSectionInvolved
Indicates that a particular section or subdivision is involved or participates in a specified relationship, process, or context.
- 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_69f76e879768819085c2fb31a6a5b44b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a006be462288190ae18e1567e2ad29f |
completed | May 10, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_6a0069e7a424819098d38458c3823605 |
completed | May 10, 2026, 11:20 a.m. |
Created at: May 3, 2026, 4:13 p.m.