Triple
T19200482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mona Best |
E470092
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Shaw |
—
|
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: Shaw | Statement: [Mona Best, familyName, Shaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shaw Context triple: [Mona Best, familyName, Shaw]
-
A.
Shaw
Shaw is a historic, culturally rich neighborhood in Washington, D.C., known for its African American heritage, jazz legacy, and vibrant urban revival.
-
B.
Shaw
chosen
Shaw is a common English and Scottish surname borne by numerous notable figures in literature, politics, and the arts.
-
C.
Shaw
Shaw is a town in the Metropolitan Borough of Oldham in Greater Manchester, England, known historically for its role in the textile industry.
-
D.
Shaw (partial)
Shaw is a historic Washington, D.C. neighborhood known for its African American cultural heritage, vibrant arts and nightlife, and significant role in the city’s civil rights history.
-
E.
Shaffer
Shaffer is a surname of English origin borne by various notable individuals across fields such as literature, law, and the arts.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f997879c8190ae7618d1ba0cede9 |
completed | April 20, 2026, 10:01 a.m. |
Created at: April 10, 2026, 12:07 p.m.