Triple
T64899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Analog |
E1290
|
entity |
| Predicate | manufactures |
P490
|
FINISHED |
| Object | analog semiconductor products |
—
|
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: analog semiconductor products | Statement: [Analog, manufactures, analog semiconductor products]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manufactures Context triple: [Analog, manufactures, analog semiconductor products]
-
A.
produces
chosen
Indicates that one entity creates, generates, or yields another entity as a result or output.
-
B.
typicalProductionType
Indicates the usual or characteristic type of production activity associated with an entity.
-
C.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
D.
commercializedIn
Indicates that something has been brought to market or made available for commercial sale or use within a specified place or context.
-
E.
designedIn
Indicates that something was created, planned, or conceived during a particular time period or at a specific location.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2516eda54819090f5c14384d4eab1 |
completed | Feb. 28, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69a24ea5c140819080409a968c8d2ce8 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.