Triple
T9968232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Beall |
E195737
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Castle |
E178779
|
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: Castle | Statement: [Will Beall, notableWork, Castle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Castle Context triple: [Will Beall, notableWork, Castle]
-
A.
Castle
chosen
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.
-
B.
Castle
Castle is a UK pub brand operated by Mitchells & Butlers, typically associated with stylish, contemporary pubs in urban locations.
-
C.
Castell
Castell is a small historic market town in northern Bavaria, Germany, known for its winegrowing tradition and association with the noble House of Castell.
-
D.
Haunted Castle
Haunted Castle is a dark ride attraction at the Santa Cruz Beach Boardwalk that takes visitors through a series of spooky, haunted-themed scenes and effects.
-
E.
Castle ward
Castle ward is an electoral ward and local administrative area within the city of Swansea in Wales.
- 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_69ca82ebd1288190912f9e4482d1fa35 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb71f9d7c8190ac02c53052c1c6ad |
completed | April 2, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d23db701b881909bb986a32df4349b |
completed | April 5, 2026, 10:47 a.m. |
Created at: March 30, 2026, 8:47 p.m.