Triple
T10728726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter H. Raven |
E253017
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Raven
Raven is the surname of American botanist and environmentalist Peter H. Raven, renowned for his work in plant systematics and biodiversity conservation.
|
E883376
|
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: Raven | Statement: [Peter H. Raven, familyName, Raven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raven Context triple: [Peter H. Raven, familyName, Raven]
-
A.
Raven
Raven is a powerful, empathic half-demon sorceress and core member of the Teen Titans, known for her dark, reserved personality and struggle to control her immense magical abilities.
-
B.
Raven
Raven is the mascot representing Sequoia High School’s athletic teams and school spirit.
-
C.
Raven
Raven is a fictional character who appears in the comic series "Old Wounds," serving as a key figure in its narrative.
-
D.
Raven
Raven is a component or section within the work "The Art of Doing Nothing," likely contributing a distinct thematic or narrative element to the overall piece.
-
E.
Raven
Raven is a central trickster-creator figure in Haida mythology, known for shaping the world and bringing light and knowledge to humanity.
- 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: Raven Triple: [Peter H. Raven, familyName, Raven]
Generated description
Raven is the surname of American botanist and environmentalist Peter H. Raven, renowned for his work in plant systematics and biodiversity conservation.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Raven Target entity description: Raven is the surname of American botanist and environmentalist Peter H. Raven, renowned for his work in plant systematics and biodiversity conservation.
-
A.
Raven
Raven is a powerful, empathic half-demon sorceress and core member of the Teen Titans, known for her dark, reserved personality and struggle to control her immense magical abilities.
-
B.
Raven
Raven is a central trickster-creator figure in Haida mythology, known for shaping the world and bringing light and knowledge to humanity.
-
C.
Raven
Raven is the mascot representing Sequoia High School’s athletic teams and school spirit.
-
D.
Raven
Raven is a fictional character who appears in the comic series "Old Wounds," serving as a key figure in its narrative.
-
E.
Raven
Raven is a component or section within the work "The Art of Doing Nothing," likely contributing a distinct thematic or narrative element to the overall piece.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70fc92a18819089cc67afee1c9b96 |
completed | April 9, 2026, 2:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de22a97fec8190bb97f68353c2144e |
completed | April 14, 2026, 11:19 a.m. |
| NEDg | Description generation | batch_69de271ca4f081908d78a20b25ebd25c |
completed | April 14, 2026, 11:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69de2ccee0cc8190acd24d5c225f7cde |
completed | April 14, 2026, 12:02 p.m. |
Created at: April 8, 2026, 9:14 p.m.