Triple
T21493413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Top Dawg Entertainment |
E530291
|
entity |
| Predicate | signedArtist |
P16560
|
FINISHED |
| Object | SiR |
—
|
NE NERFINISHED |
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: SiR | Statement: [Top Dawg Entertainment, signedArtist, SiR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SiR Context triple: [Top Dawg Entertainment, signedArtist, SiR]
-
A.
SiR
chosen
SiR is an American R&B singer, songwriter, and producer known for his smooth, soulful sound and work with Top Dawg Entertainment.
-
B.
SIRO
SIRO is a lifestyle hotel and fitness brand developed by Kerzner International that focuses on immersive wellness, performance, and recovery experiences for guests.
-
C.
SIRG
SIRG is the commonly used acronym for the Summit Implementation Review Group, a body that monitors and evaluates the execution of commitments made at hemispheric summits.
-
D.
Si
Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
-
E.
SIR
SIR is an educational program that engages students in guided inquiry and research-based learning experiences.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea54fb608190a147cd8aa6d6d04b |
completed | April 23, 2026, 9:45 a.m. |
Created at: April 16, 2026, 6:23 p.m.