Triple
T9999031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bob Brown |
E197275
|
entity |
| Predicate | hasDaughter |
P24357
|
FINISHED |
| Object |
Serena Brown
Serena Brown is the daughter of Bob Brown.
|
E833893
|
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: Serena Brown | Statement: [Bob Brown, hasDaughter, Serena Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serena Brown Context triple: [Bob Brown, hasDaughter, Serena Brown]
-
A.
Serena Evans
Serena Evans is a British actress best known for her role in the BBC sitcom "The Thin Blue Line."
-
B.
Serena Southerlyn
Serena Southerlyn is a fictional Assistant District Attorney on the long-running television series "Law & Order," known for her idealism and strong moral convictions in prosecuting cases.
-
C.
Serena Powers
Serena Powers is a relatively obscure individual whose specific public achievements or background are not widely documented.
-
D.
Serena Joy Waterford
Serena Joy Waterford is the strict, embittered Wife of a high-ranking Commander in Margaret Atwood’s "The Handmaid’s Tale," known for her complicity in and enforcement of Gilead’s oppressive regime.
-
E.
Serena Ryder
Serena Ryder is a Canadian singer-songwriter known for her soulful vocals and genre-blending folk, rock, and pop music.
- 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: Serena Brown Triple: [Bob Brown, hasDaughter, Serena Brown]
Generated description
Serena Brown is the daughter of Bob Brown.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serena Brown Target entity description: Serena Brown is the daughter of Bob Brown.
-
A.
Serena Evans
Serena Evans is a British actress best known for her role in the BBC sitcom "The Thin Blue Line."
-
B.
Serena Southerlyn
Serena Southerlyn is a fictional Assistant District Attorney on the long-running television series "Law & Order," known for her idealism and strong moral convictions in prosecuting cases.
-
C.
Serena Powers
Serena Powers is a relatively obscure individual whose specific public achievements or background are not widely documented.
-
D.
Serena Joy Waterford
Serena Joy Waterford is the strict, embittered Wife of a high-ranking Commander in Margaret Atwood’s "The Handmaid’s Tale," known for her complicity in and enforcement of Gilead’s oppressive regime.
-
E.
Serena Ryder
Serena Ryder is a Canadian singer-songwriter known for her soulful vocals and genre-blending folk, rock, and pop music.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8c78448190a5332f4ff8a7b3dd |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2584bd6cc8190841353847dd2f00c |
completed | April 5, 2026, 12:40 p.m. |
| NEDg | Description generation | batch_69d259016fb08190aadf9d4cee0b42d7 |
completed | April 5, 2026, 12:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d259a2e48481908bd8e4829f676618 |
completed | April 5, 2026, 12:46 p.m. |
Created at: March 30, 2026, 8:51 p.m.