Triple
T8629643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanley Miller |
E204367
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Stanley |
E123677
|
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: Stanley | Statement: [Stanley Miller, givenName, Stanley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanley Context triple: [Stanley Miller, givenName, Stanley]
-
A.
Stanley
Stanley is the given first name of Ann Dunham, the American anthropologist and mother of former U.S. President Barack Obama.
-
B.
Stanley
chosen
Stanley is a masculine given name of Old English origin that has been borne by numerous notable figures, including British statesman Stanley Baldwin.
-
C.
Stanley
Stanley is a village located within the Borough of Erewash in Derbyshire, England.
-
D.
Stanley
Stanley is a coastal town on the southern side of Hong Kong Island known for its market, beaches, and popular tourist promenade.
-
E.
Stanley
Stanley is a small village in Perth and Kinross, Scotland, situated on the banks of the River Tay and known historically for its cotton mill and scenic riverside setting.
- 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_69ca834a4ea0819094970dceb9e389f3 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47406efc8190b559c68764b7455d |
completed | March 31, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebc0acf508190a090fb1edf9420d2 |
completed | April 2, 2026, 6:57 p.m. |
Created at: March 30, 2026, 6:27 p.m.