Triple
T1952149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Brown |
E42181
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Brown |
E101694
|
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: Brown | Statement: [James Brown, familyName, Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brown Context triple: [James Brown, familyName, Brown]
-
A.
Brown
chosen
Brown is a common English-language surname of Anglo-Saxon origin, typically derived from a nickname referring to hair color, complexion, or clothing.
-
B.
Maroon
Maroon refers to the descendants of escaped African slaves in the Americas who formed independent communities, notably in places like Suriname and Jamaica, preserving distinct African-derived cultures and traditions.
-
C.
Gray
Gray is the commonly used short form of the name Gray Davis, the former governor of California.
-
D.
Gray
Gray is a historic commune in eastern France known for its picturesque setting along the Saône River and its well-preserved old town.
-
E.
Brown Base
Brown Base is an Argentine research station in Antarctica that operates seasonally to support scientific studies in the region.
- 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_69a8870e08fc8190a319cbf2600db15f |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb34eb5748190a3ac395252951eba |
completed | March 7, 2026, 5:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbc611fc8190b2f512c744cbc364 |
completed | March 8, 2026, 10:44 p.m. |
Created at: March 4, 2026, 7:36 p.m.