Triple
T9880202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saweetie |
E180780
|
entity |
| Predicate | notableSingle |
P3283
|
FINISHED |
| Object | ICY GRL |
E826962
|
NE 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: ICY GRL | Statement: [Saweetie, notableSingle, ICY GRL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ICY GRL Context triple: [Saweetie, notableSingle, ICY GRL]
-
A.
ICY GRL
chosen
"ICY GRL" is Saweetie’s breakout hip-hop single that gained viral popularity and helped launch her mainstream music career.
-
B.
Gla
Gla is a large fortified Mycenaean archaeological site in Boeotia, Greece, notable for its massive walls and strategic position overlooking the former Lake Kopais.
-
C.
Glover
Glover is a surname of English origin borne by various notable individuals across fields such as politics, sports, and the arts.
-
D.
ICE T
ICE T is a tilting high-speed train variant of Germany’s InterCityExpress fleet designed for faster travel on curving conventional lines.
-
E.
GIO
GIO is an Australian insurance company best known for providing a wide range of general insurance products, including car, home, and business insurance.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca828082cc8190a40f8d299caa6545 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb4146fe881908f9fc553dfca31e1 |
completed | April 2, 2026, 12:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eaea3d788190b3020c07c2739495 |
completed | April 5, 2026, 4:54 a.m. |
Created at: March 30, 2026, 8:38 p.m.