Triple
T4880795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nina Agdal |
E109320
|
entity |
| Predicate | hasWorkedFor |
P11675
|
FINISHED |
| Object |
Bebe
Bebe is a contemporary women's fashion brand known for its trendy, body-conscious clothing and accessories.
|
E477090
|
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: Bebe | Statement: [Nina Agdal, hasWorkedFor, Bebe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bebe Context triple: [Nina Agdal, hasWorkedFor, Bebe]
-
A.
Beba
Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
-
B.
Bebek
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
-
C.
Bebe Buell
Bebe Buell is an American model and singer known for her work as a 1970s fashion icon and for her high-profile relationships in the rock music scene.
-
D.
Becky
Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
-
E.
Becca
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
- 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: Bebe Triple: [Nina Agdal, hasWorkedFor, Bebe]
Generated description
Bebe is a contemporary women's fashion brand known for its trendy, body-conscious clothing and accessories.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bebe Target entity description: Bebe is a contemporary women's fashion brand known for its trendy, body-conscious clothing and accessories.
-
A.
Beba
Beba is a city in Egypt’s Beni Suef Governorate, known as a local administrative and commercial center in the region.
-
B.
Bebek
Bebek is an upscale seaside neighborhood on Istanbul’s Bosphorus shore, known for its scenic views, cafes, and vibrant social life.
-
C.
Bebe Buell
Bebe Buell is an American model and singer known for her work as a 1970s fashion icon and for her high-profile relationships in the rock music scene.
-
D.
Becky
Becky is a common English feminine given name, typically used as a diminutive of Rebecca.
-
E.
Becca
Becca is a central character in the 2015 horror film "The Visit," a teenage girl who documents her and her brother’s unsettling stay with their estranged grandparents.
- 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_69bd440e9d64819083e82cf33b4d9570 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6dc071d4819083ea9fd0c73c5f49 |
completed | March 20, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be6803a1c081908972984241276c19 |
completed | March 21, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69be6aadda048190a5b9276f59080b3e |
completed | March 21, 2026, 9:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be6b0e7ca08190861992a251b3dbd9 |
completed | March 21, 2026, 9:55 a.m. |
Created at: March 20, 2026, 1:27 p.m.