Triple
T13531678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wacoal |
E323147
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object |
Wing
Wing is a Japanese lingerie and intimate apparel brand known for its comfortable, everyday undergarments for women.
|
E1045540
|
NE FINISHED |
How this triple was built (4 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: Wing | Statement: [Wacoal, hasBrand, Wing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wing Context triple: [Wacoal, hasBrand, Wing]
-
A.
Wing
Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
-
B.
Wing
Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
-
C.
One Wing
"One Wing" is an emotional R&B ballad by American singer Jordin Sparks that showcases her powerful vocals and explores themes of heartbreak and resilience.
-
D.
Big Wing
Big Wing was a World War II Royal Air Force fighter tactic that involved massing large formations of fighters to intercept enemy raids, most notably during the Battle of Britain.
-
E.
New Wing
New Wing is a later Baroque extension of Berlin’s Charlottenburg Palace, known for its richly decorated state apartments and royal ceremonial rooms.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wing Triple: [Wacoal, hasBrand, Wing]
Generated description
Wing is a Japanese lingerie and intimate apparel brand known for its comfortable, everyday undergarments for women.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wing Target entity description: Wing is a Japanese lingerie and intimate apparel brand known for its comfortable, everyday undergarments for women.
-
A.
Wing
Wing is an experimental mobile operating system and user interface project developed by X (formerly Google X) to explore new paradigms in smartphone interaction and design.
-
B.
Wing
Wing is an Alphabet Inc. subsidiary focused on developing and operating drone-based delivery services and related logistics technologies.
-
C.
One Wing
"One Wing" is an emotional R&B ballad by American singer Jordin Sparks that showcases her powerful vocals and explores themes of heartbreak and resilience.
-
D.
Big Wing
Big Wing was a World War II Royal Air Force fighter tactic that involved massing large formations of fighters to intercept enemy raids, most notably during the Battle of Britain.
-
E.
New Wing
New Wing is a later Baroque extension of Berlin’s Charlottenburg Palace, known for its richly decorated state apartments and royal ceremonial rooms.
- F. None of above. chosen
Provenance (5 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. |
| NEDg | Description generation | batch_69f7565846108190bb6550505af8ac5d |
completed | May 3, 2026, 2:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75a2107e081909fd00af67938f2e9 |
completed | May 3, 2026, 2:22 p.m. |
Created at: April 9, 2026, 9:44 p.m.