Triple
T22203834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rishton |
E548749
|
entity |
| Predicate | timeZoneDST |
P109
|
FINISHED |
| Object | BST |
—
|
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: BST | Statement: [Rishton, timeZoneDST, BST]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BST Context triple: [Rishton, timeZoneDST, BST]
-
A.
BST
BST is the time zone used throughout Bangladesh, set six hours ahead of Coordinated Universal Time (UTC+6).
-
B.
BST
chosen
BST (British Summer Time) is the daylight saving time observed in the United Kingdom, set one hour ahead of Coordinated Universal Time (UTC+1) during the summer months.
-
C.
AVL tree
An AVL tree is a self-balancing binary search tree data structure that maintains strict height balance to ensure efficient insertion, deletion, and lookup operations.
-
D.
B-tree
A B-tree is a self-balancing tree data structure that maintains sorted data and allows efficient insertion, deletion, and search operations, commonly used to implement database indexes.
-
E.
AVL
AVL is the three-letter IATA airport code for Asheville Regional Airport serving the Asheville, North Carolina area.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b25eac4819094b3c50027ed66db |
completed | April 28, 2026, 9:48 p.m. |
Created at: April 16, 2026, 8:36 p.m.