Triple
T23297033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward H. Seymour |
E590200
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Seymour |
—
|
NE NERFINISHED |
How this triple was built (2 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: Seymour | Statement: [Edward H. Seymour, hasFamilyName, Seymour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seymour Context triple: [Edward H. Seymour, hasFamilyName, Seymour]
-
A.
Seymour
chosen
Seymour is a masculine given name of English origin that has been borne by various notable figures in fields such as business, politics, and the arts.
-
B.
Seymour
Seymour is a small town in New Haven County, Connecticut, known for its historic industrial roots along the Naugatuck River.
-
C.
Seymour
Seymour is a regional town in central Victoria, Australia, known as a key agricultural and transport hub on the route between Melbourne and Sydney.
-
D.
Seymour
Seymour is a small unincorporated community and suburban area in eastern Tennessee, situated near Knoxville in the foothills of the Great Smoky Mountains.
-
E.
Seymour
Seymour is a socially awkward, middle-aged record collector who becomes a central figure in the coming-of-age graphic novel and film "Ghost World."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196cfc79081909966638cec48cf60 |
completed | April 29, 2026, 5:27 a.m. |
Created at: April 17, 2026, 5:03 p.m.