Triple
T13602760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philip Anthony Hopkins |
E324984
|
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: [Philip Anthony Hopkins, familyName, Hopkins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hopkins Context triple: [Philip Anthony 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.
Hopkins
Hopkins is a small suburban city in Minnesota located just west of Minneapolis.
-
C.
Hopkins
Hopkins is a coastal Garifuna village in Belize known for its vibrant Afro-Caribbean culture, drumming traditions, and access to nearby reefs and rainforest.
-
D.
Hopkin
Hopkin is a surname and given name of English and Welsh origin, often considered a variant of Hopkins.
-
E.
Kogod
Kogod is the business school of American University in Washington, D.C., offering undergraduate and graduate programs in business and management.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07ca07481909c45da551ea61ab4 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f92224c8190b66adef1291cd47f |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:49 p.m.