Triple
T38222337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US Patent 4,750 |
E1012043
|
entity |
| Predicate | technologicalArea |
P19268
|
FINISHED |
| Object | mechanization of sewing |
—
|
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: mechanization of sewing | Statement: [US Patent 4,750, technologicalArea, mechanization of sewing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: technologicalArea Context triple: [US Patent 4,750, technologicalArea, mechanization of sewing]
-
A.
innovationArea
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
B.
technologyField
chosen
Indicates the area or domain of technology in which an entity is involved, specialized, or categorized.
-
C.
hasTechnologicalActivity
Indicates that an entity engages in, performs, or is involved in some form of technological process, operation, or practice.
-
D.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
-
E.
supportsTechnologyArea
Indicates that one entity provides backing, resources, or endorsement for a particular technology area associated with another entity.
- 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_69f76dd25e0c81909f2abd0803e5e3ee |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
Created at: May 3, 2026, 4:30 p.m.