Triple
T1311639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esek Hopkins |
E28004
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hopkins |
E49177
|
NE FINISHED |
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: Hopkins | Statement: [Esek Hopkins, familyName, Hopkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hopkins Context triple: [Esek Hopkins, familyName, Hopkins]
-
A.
Hopkins
chosen
Hopkins is a common English and Welsh surname borne by numerous notable figures across politics, the arts, and academia.
-
B.
Johns Hopkins
Johns Hopkins was a 19th-century American Quaker businessman, investor, and philanthropist whose bequests led to the creation of Johns Hopkins University and Johns Hopkins Hospital.
-
C.
Belmont
Belmont is a suburban town in Middlesex County, Massachusetts, known for its residential character and proximity to Boston.
-
D.
Belmont
Belmont is a city on the San Francisco Peninsula in California, known for its suburban character, hilly terrain, and proximity to major Bay Area tech and transportation hubs.
-
E.
Belmont
Belmont is a predominantly residential neighborhood in the central Bronx, New York City, historically known as the borough’s “Little Italy” for its Italian-American community and businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a498532c3481909223b74af2e578df |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1560f888190bdd9107b08395e0b |
completed | March 1, 2026, 10:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acbaec736881909645919764d73f5f |
completed | March 7, 2026, 11:55 p.m. |
Created at: March 1, 2026, 7:55 p.m.