Triple
T15099143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoox Net-a-Porter Group |
E360615
|
entity |
| Predicate | formedByMergerOf |
P77
|
FINISHED |
| Object |
Yoox
Yoox is an Italian online fashion retailer known for offering discounted designer clothing, accessories, and lifestyle products through its e-commerce platform.
|
E360615
|
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: Yoox | Statement: [Yoox Net-a-Porter Group, formedByMergerOf, Yoox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yoox Context triple: [Yoox Net-a-Porter Group, formedByMergerOf, Yoox]
-
A.
Yoox Net-a-Porter Group
Yoox Net-a-Porter Group is a leading global online luxury fashion retailer formed from the merger of Yoox and Net-a-Porter, known for selling high-end designer brands through multiple e-commerce platforms.
-
B.
Zara
Zara is the historical Italian name for the coastal Croatian city of Zadar on the Adriatic Sea.
-
C.
Zara
Zara is a character in the 1953 film noir "Pickup on South Street," involved in the story’s underworld of espionage and crime.
-
D.
Zara
Zara is a town and district in Turkey known for its location in the eastern part of the Central Anatolia region.
-
E.
Zara
Zara is a global fast-fashion retail brand known for rapidly translating runway trends into affordable clothing and accessories for a mass-market audience.
- 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: Yoox Triple: [Yoox Net-a-Porter Group, formedByMergerOf, Yoox]
Generated description
Yoox is an Italian online fashion retailer known for offering discounted designer clothing, accessories, and lifestyle products through its e-commerce platform.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yoox Target entity description: Yoox is an Italian online fashion retailer known for offering discounted designer clothing, accessories, and lifestyle products through its e-commerce platform.
-
A.
Yoox Net-a-Porter Group
chosen
Yoox Net-a-Porter Group is a leading global online luxury fashion retailer formed from the merger of Yoox and Net-a-Porter, known for selling high-end designer brands through multiple e-commerce platforms.
-
B.
Zara
Zara is the historical Italian name for the coastal Croatian city of Zadar on the Adriatic Sea.
-
C.
Zara
Zara is a character in the 1953 film noir "Pickup on South Street," involved in the story’s underworld of espionage and crime.
-
D.
Zara
Zara is a town and district in Turkey known for its location in the eastern part of the Central Anatolia region.
-
E.
Zara
Zara is a global fast-fashion retail brand known for rapidly translating runway trends into affordable clothing and accessories for a mass-market audience.
- F. None of above.
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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0054f00388190a5123d9f4a869b96 |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae230d148190a343ac92fb089902 |
completed | May 9, 2026, 3:46 a.m. |
| NEDg | Description generation | batch_69feb0551a508190802f4073fa5ae4b4 |
completed | May 9, 2026, 3:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb11fa1b081909243679603194b0b |
completed | May 9, 2026, 3:59 a.m. |
Created at: April 10, 2026, 3:04 a.m.