Triple
T21795743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DBApparel |
E538088
|
entity |
| Predicate | brandPortfolioIncludes |
P18121
|
FINISHED |
| Object |
Bellinda
Bellinda is a hosiery and underwear brand known for offering affordable everyday legwear and lingerie products in European markets.
|
E1502974
|
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: Bellinda | Statement: [DBApparel, brandPortfolioIncludes, Bellinda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bellinda Context triple: [DBApparel, brandPortfolioIncludes, Bellinda]
-
A.
Sandra
Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
-
B.
Sandra
Sandra is a German pop singer best known for her 1980s Eurodisco hits such as "Maria Magdalena" and "In the Heat of the Night."
-
C.
Sandra
Sandra is a 1965 Italian drama film by Luchino Visconti, noted for its modern reworking of the Electra myth and its exploration of family secrets and guilt.
-
D.
Sandra
Sandra is a feminine given name of Greek origin meaning "defender of mankind," commonly used in many English-speaking and European countries.
-
E.
Sandra
Sandra is a fictional character portrayed by English actress Annabelle Wallis.
- 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: Bellinda Triple: [DBApparel, brandPortfolioIncludes, Bellinda]
Generated description
Bellinda is a hosiery and underwear brand known for offering affordable everyday legwear and lingerie products in European markets.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bellinda Target entity description: Bellinda is a hosiery and underwear brand known for offering affordable everyday legwear and lingerie products in European markets.
-
A.
Sandra
Sandra is a 1965 Italian drama film by Luchino Visconti, noted for its modern reworking of the Electra myth and its exploration of family secrets and guilt.
-
B.
Sandra
Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
-
C.
Sandra
Sandra is a German pop singer best known for her 1980s Eurodisco hits such as "Maria Magdalena" and "In the Heat of the Night."
-
D.
Sandra
Sandra is a feminine given name of Greek origin meaning "defender of mankind," commonly used in many English-speaking and European countries.
-
E.
Sandra
Sandra is a fictional character portrayed by English actress Annabelle Wallis.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f06223ecc48190bd3b173586ea7818 |
completed | April 28, 2026, 7:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a3e7e3b508190bccf7bfd6856861a |
completed | May 17, 2026, 10:17 p.m. |
| NEDg | Description generation | batch_6a0a4292891c8190a9d6202faa3eeb95 |
completed | May 17, 2026, 10:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a433f4528819099527393c5966cbb |
completed | May 17, 2026, 10:37 p.m. |
Created at: April 16, 2026, 6:53 p.m.