Triple
T5784286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Urban Music Album |
E128230
|
entity |
| Predicate | hasAwardLanguage |
P63553
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Best Urban Music Album, hasAwardLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAwardLanguage Context triple: [Best Urban Music Album, hasAwardLanguage, Spanish]
-
A.
awardNameLanguage
Indicates the language in which the name of an award is expressed.
-
B.
awardLanguage
chosen
Indicates that an award is given specifically for works or achievements in a particular language.
-
C.
hasAwardConnection
Indicates a relationship where an entity is connected to an award, such as by receiving, being nominated for, or otherwise associated with that award.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
winnerLanguage
Indicates that the associated language is the one used by, or officially recognized for, the winner in a given contest, award, or competitive event.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a19870c819084dc68b36b0cdd60 |
completed | March 22, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.