Triple
T14350179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pretty Toney Album |
E355831
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Shawn Wigs |
E1060683
|
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: Shawn Wigs | Statement: [The Pretty Toney Album, featuresArtist, Shawn Wigs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shawn Wigs Context triple: [The Pretty Toney Album, featuresArtist, Shawn Wigs]
-
A.
Wigs
chosen
Wigs is a rapper associated with the hip-hop collective Theodore Unit, known for its close ties to Ghostface Killah and the Wu-Tang Clan.
-
B.
The Hair Buyer
The Hair Buyer is a character from the musical "Hamilton," known for purchasing Eliza Hamilton’s hair in the song "Burn."
-
C.
Wig in a Box
"Wig in a Box" is a standout musical number from the rock musical *Hedwig and the Angry Inch*, celebrated for its blend of glam-rock energy and emotional self-discovery.
-
D.
Bangs
Bangs is a surname of English origin borne by various notable individuals, including scientists, writers, and public figures.
-
E.
Wiggi
Wiggi is a diminutive nickname commonly used in German for the given name Ludwig.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c4335e481909d4db39b8d25edc9 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:14 a.m.