Triple
T205957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bobby Brown |
E4610
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Brown |
E5209
|
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: [Bobby Brown, familyName, Brown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brown Context triple: [Bobby Brown, familyName, Brown]
-
A.
Orange
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
B.
Black
Black is a nominative report series of early United States Supreme Court decisions compiled and published under the name of the court reporter Black.
-
C.
Black
chosen
Black is a common English-language surname borne by numerous notable individuals across diverse fields.
-
D.
Case White
Case White was the German codename for the 1939 invasion of Poland that marked the beginning of World War II in Europe.
-
E.
Tiffany Blue
Tiffany Blue is the distinctive light robin’s-egg blue color trademarked and famously used by the luxury jewelry brand Tiffany & Co.
- 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c04e42481909e957cb34dc02731 |
completed | Feb. 28, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a32bc77734819095e6cf53a10aa3d8 |
completed | Feb. 28, 2026, 5:54 p.m. |
Created at: Feb. 28, 2026, 2:51 a.m.