Triple
T23298705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freygish |
E590241
|
entity |
| Predicate | hasTypicalUseOn |
P37480
|
FINISHED |
| Object | minor tonic |
—
|
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: minor tonic | Statement: [Freygish, hasTypicalUseOn, minor tonic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalUseOn Context triple: [Freygish, hasTypicalUseOn, minor tonic]
-
A.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
hasTypicalUseContext
chosen
Indicates that something is commonly or characteristically used within a particular situation, setting, or context.
-
C.
isSometimesUsedFor
Indicates that something serves a particular purpose or function on some occasions, but not consistently or exclusively.
-
D.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
-
E.
isFamouslyUsedBy
Indicates that something is widely and notably used by a particular person, group, or entity, in a way that is broadly recognized or associated with them.
- 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_69e25d1c0ecc8190a355aa229f06d0e0 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196d133448190bf350a9f51c1531c |
completed | April 29, 2026, 5:27 a.m. |
| PD | Predicate disambiguation | batch_69effcf325f88190b320268c3c551abb |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 5:03 p.m.