Triple
T10382852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sissy Spacek |
E244684
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Castle Rock |
E103959
|
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 Rock | Statement: [Sissy Spacek, notableWork, Castle Rock]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Castle Rock Context triple: [Sissy Spacek, notableWork, Castle Rock]
-
A.
Castle Rock
Castle Rock is the prominent volcanic crag in Edinburgh that forms the dramatic natural foundation of Edinburgh Castle.
-
B.
Castle Rock
Castle Rock is a prominent sandstone outcrop in Nottingham, England, historically significant as the elevated site on which Nottingham Castle was built.
-
C.
Castle Rock
Castle Rock is a rapidly growing commuter town in central Colorado known for its distinctive castle-shaped butte and family-oriented suburban character between Denver and Colorado Springs.
-
D.
Castle Rock
chosen
Castle Rock is a psychological horror television series inspired by the interconnected universe of Stephen King’s stories, released as an original program on Hulu.
-
E.
Castle Rock, Maine
Castle Rock, Maine is a fictional small town in Stephen King’s works, known as the setting for many of his horror and suspense stories.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e992d8e08190aaa9a04925f52ccc |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7959b6c2c819085b606280024c0f9 |
completed | April 9, 2026, 12:03 p.m. |
Created at: April 6, 2026, 12:04 p.m.