Triple
T2577748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanessa Bell |
E57015
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Stephen
Stephen is the maiden surname of English painter and interior designer Vanessa Bell, a central figure in the Bloomsbury Group.
|
E281078
|
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: Stephen | Statement: [Vanessa Bell, familyName, Stephen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen Context triple: [Vanessa Bell, familyName, Stephen]
-
A.
Stephen
Stephen is the formal given name of Steve Wozniak, the American computer engineer and co-founder of Apple Inc.
-
B.
Stephen
Stephen is the middle name of Harold Stephen Black, an American electrical engineer known for inventing the negative feedback amplifier.
-
C.
Stephen
Stephen is the full given name of former Scottish footballer and manager Steve Nicol, best known for his successful career with Liverpool FC in the 1980s and early 1990s.
-
D.
Stephen
Stephen is the first name of British television writer and producer Russell T Davies, best known for reviving the science fiction series Doctor Who.
-
E.
Stephen
Stephen is a masculine given name of Greek origin meaning "crown" or "garland," widely used in English-speaking countries.
- 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: Stephen Triple: [Vanessa Bell, familyName, Stephen]
Generated description
Stephen is the maiden surname of English painter and interior designer Vanessa Bell, a central figure in the Bloomsbury Group.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stephen Target entity description: Stephen is the maiden surname of English painter and interior designer Vanessa Bell, a central figure in the Bloomsbury Group.
-
A.
Stephen
chosen
Stephen is the birth surname of the English modernist writer Virginia Woolf, belonging to a prominent literary and intellectual family in late 19th-century London.
-
B.
Stephen
Stephen is the given first name of Steve Wynn, the American real estate businessman and art collector known for his role in developing major Las Vegas casinos.
-
C.
Stephen
Stephen is the given first name of Steve Case, the American entrepreneur and co-founder of AOL.
-
D.
Stephen
Stephen is the first name of British television writer and producer Russell T Davies, best known for reviving the science fiction series Doctor Who.
-
E.
Stephen
Stephen is the given name of Stephen G. Breyer, an American jurist and former Associate Justice of the U.S. Supreme Court.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a73a508190bf12e889a5d4bbf3 |
completed | March 7, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af907510d481909e7c5e5207d17774 |
completed | March 10, 2026, 3:31 a.m. |
| NEDg | Description generation | batch_69af91f3cab88190b18fc5a02b66bfdb |
completed | March 10, 2026, 3:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af927bb1d0819081ab11eb4470e28d |
completed | March 10, 2026, 3:39 a.m. |
Created at: March 6, 2026, 9:49 p.m.