Triple
T4246175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweat |
E95532
|
entity |
| Predicate | hasSisterAlbum |
P54924
|
FINISHED |
| Object | Suit |
—
|
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: Suit | Statement: [Sweat, hasSisterAlbum, Suit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSisterAlbum Context triple: [Sweat, hasSisterAlbum, Suit]
-
A.
hasSister
Indicates that one entity is the sister of another entity.
-
B.
hasSisterPublication
Indicates that one publication is related to another as a sister publication, typically under the same parent organization or closely associated in scope or branding.
-
C.
hasPartInDiscography
Indicates that an entity (such as a song, album, or track) is included as a component within another entity’s discography.
-
D.
hasSisterChair
Indicates that one chair is related to another chair as its sister, typically implying a closely associated or counterpart chair within the same set or context.
-
E.
hasSisterDistrict
Indicates that one district is designated as a sister district to another, typically reflecting a formal partnership or cooperative relationship between them.
- F. None of above. chosen
Provenance (4 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_69b3453d91548190b4d4ef8fe52aa2ac |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e8db5bc8190873c5ae3753aaa58 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f587148190a1830503459939b6 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:05 p.m.