Triple
T12668315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hail Holy Queen |
E302613
|
entity |
| Predicate | hasStyleInSisterAct |
P1609
|
FINISHED |
| Object | Gospel-influenced choral arrangement |
—
|
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: Gospel-influenced choral arrangement | Statement: [Hail Holy Queen, hasStyleInSisterAct, Gospel-influenced choral arrangement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStyleInSisterAct Context triple: [Hail Holy Queen, hasStyleInSisterAct, Gospel-influenced choral arrangement]
-
A.
hasSister
Indicates that one entity is the sister of another entity.
-
B.
hasSisterChair
Indicates that one chair is related to another chair as its sister, typically implying a closely associated or counterpart chair within the same set or context.
-
C.
hasSpouseStyle
Indicates a relationship where one entity’s manner, appearance, or behavior resembles or is characteristic of another entity’s spouse.
-
D.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
E.
hasSisters
Indicates that one entity has one or more female siblings in relation to 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.