Triple
T24013425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brisker method |
E594600
|
entity |
| Predicate | typicalTool |
P29151
|
FINISHED |
| Object | chilukim (fine distinctions) |
—
|
LITERAL 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: chilukim (fine distinctions) | Statement: [Brisker method, typicalTool, chilukim (fine distinctions)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTool Context triple: [Brisker method, typicalTool, chilukim (fine distinctions)]
-
A.
typicalTools
chosen
Indicates that the related tools are commonly or characteristically used to perform the associated activity, task, or function.
-
B.
toolIn
Indicates that one entity is a tool or instrument used in or associated with another entity or context.
-
C.
toolType
Indicates the specific kind or category of tool associated with an entity.
-
D.
toolUsed
Indicates that an action or task is performed using a particular tool as the means or instrument.
-
E.
toolOrProduct
Indicates that one entity is used as a tool or produced as a product in relation to another entity or activity.
- F. None of above.
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_69e288bc8f608190ac4af29f0bd1c744 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d59ee0a08190ad1e1bc2dad1dda7 |
completed | April 29, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_69f17639d23c8190bed93434e2f9230a |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:41 p.m.