Triple
T4363902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burney Falls |
E98724
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Samuel Burney
Samuel Burney was a 19th-century settler in Northern California after whom the scenic Burney Falls in Shasta County is named.
|
E432858
|
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: Samuel Burney | Statement: [Burney Falls, namedAfter, Samuel Burney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samuel Burney Context triple: [Burney Falls, namedAfter, Samuel Burney]
-
A.
William Boyce
William Boyce was an 18th-century English composer and organist best known for his church music, symphonies, and the influential collection "Cathedral Music."
-
B.
Charles Burney
Charles Burney was an 18th-century English music historian, composer, and organist best known for his extensive writings on the history of music.
-
C.
S. M. H. Burney
S. M. H. Burney was an Indian civil servant and administrator who served as a governor in the state of Haryana.
-
D.
George Lloyd
George Lloyd was an American character actor active in the mid-20th century, appearing in numerous films and serials, often in supporting or bit roles.
-
E.
John Bevan
John Bevan was a British intelligence officer who played a key role in planning and overseeing Allied deception operations during World War II.
- 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: Samuel Burney Triple: [Burney Falls, namedAfter, Samuel Burney]
Generated description
Samuel Burney was a 19th-century settler in Northern California after whom the scenic Burney Falls in Shasta County is named.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Samuel Burney Target entity description: Samuel Burney was a 19th-century settler in Northern California after whom the scenic Burney Falls in Shasta County is named.
-
A.
William Boyce
William Boyce was an 18th-century English composer and organist best known for his church music, symphonies, and the influential collection "Cathedral Music."
-
B.
Charles Burney
Charles Burney was an 18th-century English music historian, composer, and organist best known for his extensive writings on the history of music.
-
C.
S. M. H. Burney
S. M. H. Burney was an Indian civil servant and administrator who served as a governor in the state of Haryana.
-
D.
George Lloyd
George Lloyd was an American character actor active in the mid-20th century, appearing in numerous films and serials, often in supporting or bit roles.
-
E.
John Bevan
John Bevan was a British intelligence officer who played a key role in planning and overseeing Allied deception operations during World War II.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351e70a748190af6f1b709a0e75e6 |
completed | March 12, 2026, 11:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dbc925d881909fac944bc7ce5407 |
completed | March 14, 2026, 10:06 p.m. |
| NEDg | Description generation | batch_69b5dc578b08819095cbf6ba8470d3e0 |
completed | March 14, 2026, 10:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5dd1b03508190a47bb6fb93f22ad8 |
completed | March 14, 2026, 10:11 p.m. |
Created at: March 12, 2026, 11:16 p.m.