Triple
T19865176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara Castle |
E477372
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Castle |
—
|
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: Castle | Statement: [Barbara Castle, familyName, Castle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Castle Context triple: [Barbara Castle, familyName, Castle]
-
A.
Castle
Castle is the informal name for University College, Durham, a historic constituent college of Durham University housed in Durham Castle.
-
B.
Castle
Castle is an American crime-comedy-drama television series that follows mystery novelist Richard Castle as he assists the NYPD in solving unusual homicide cases.
-
C.
Castle
chosen
Castle is a common English surname of Norman origin, typically referring to someone who lived near or worked in a castle.
-
D.
Castle
Castle is a UK pub brand operated by Mitchells & Butlers, typically associated with stylish, contemporary pubs in urban locations.
-
E.
Castle Keep
Castle Keep is a 1969 surreal anti-war film set in World War II, known for its blend of dark humor, allegory, and philosophical reflection on art and destruction.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6589eb24081908715b683de1edc68 |
completed | April 20, 2026, 4:47 p.m. |
Created at: April 10, 2026, 1:51 p.m.