Triple
T13531676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wacoal |
E323147
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Wacoal |
E323147
|
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: Wacoal | Statement: [Wacoal, hasBrand, Wacoal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wacoal Context triple: [Wacoal, hasBrand, Wacoal]
-
A.
Wacoal
chosen
Wacoal is a Japanese company best known as a leading manufacturer and retailer of women's lingerie and intimate apparel.
-
B.
Maidenform
Maidenform is a well-known American lingerie and shapewear brand recognized for its bras, panties, and intimate apparel.
-
C.
Reiss
Reiss is a German-language surname borne by various notable individuals across fields such as mountaineering, arts, and academia.
-
D.
Isabel Jeans
Isabel Jeans was a British stage and film actress known for her sophisticated roles in early 20th-century cinema, including appearances in several Alfred Hitchcock films.
-
E.
Brioni
Brioni is an Italian luxury menswear brand renowned for its high-end tailored suits and sartorial craftsmanship.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafbb34548190a6b44faa48125cd4 |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7549fc5f881908691eb62c1f5a5d5 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:44 p.m.