Triple
T8949789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Thacker |
E213315
|
entity |
| Predicate | hasFriend |
P8712
|
FINISHED |
| Object |
Bella
Bella is a close friend of William Thacker, the fictional London bookseller portrayed by Hugh Grant in the romantic comedy film "Notting Hill."
|
E768327
|
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: Bella | Statement: [William Thacker, hasFriend, Bella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bella Context triple: [William Thacker, hasFriend, Bella]
-
A.
Bella
Bella is the main human protagonist of the Twilight series, known for her introspective nature and complex relationship with the supernatural world.
-
B.
Bella
Bella is a 2006 independent drama film starring Tammy Blanchard that explores themes of love, redemption, and unexpected family.
-
C.
Bella
Bella is the given name of Australian actress Bella Heathcote, known for her roles in film and television.
-
D.
Bella Greene
Bella Greene is a relatively obscure individual whose specific public achievements or background are not widely documented.
-
E.
Esme
Esme is a song by Joanna Newsom from her 2010 album "Have One on Me," noted for its intricate harp arrangements and poetic lyrics.
- 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: Bella Triple: [William Thacker, hasFriend, Bella]
Generated description
Bella is a close friend of William Thacker, the fictional London bookseller portrayed by Hugh Grant in the romantic comedy film "Notting Hill."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bella Target entity description: Bella is a close friend of William Thacker, the fictional London bookseller portrayed by Hugh Grant in the romantic comedy film "Notting Hill."
-
A.
Bella
Bella is the main human protagonist of the Twilight series, known for her introspective nature and complex relationship with the supernatural world.
-
B.
Bella
Bella is a 2006 independent drama film starring Tammy Blanchard that explores themes of love, redemption, and unexpected family.
-
C.
Bella
Bella is the given name of Australian actress Bella Heathcote, known for her roles in film and television.
-
D.
Bella Greene
Bella Greene is a relatively obscure individual whose specific public achievements or background are not widely documented.
-
E.
Esme
Esme is a song by Joanna Newsom from her 2010 album "Have One on Me," noted for its intricate harp arrangements and poetic lyrics.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670b5f50819080f1c73992fe5281 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc206550c8190abf016f25b14fa64 |
completed | April 3, 2026, 1:35 p.m. |
| NEDg | Description generation | batch_69cfc3f170a08190a2cab07eb280ee3b |
completed | April 3, 2026, 1:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfc476204481909f0baaf400483f33 |
completed | April 3, 2026, 1:45 p.m. |
Created at: March 30, 2026, 6:59 p.m.