Triple
T4206896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dow Corning Corporation |
E93803
|
entity |
| Predicate | hasTechnologyFocus |
P19268
|
FINISHED |
| Object | silicone chemistry |
—
|
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: silicone chemistry | Statement: [Dow Corning Corporation, hasTechnologyFocus, silicone chemistry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTechnologyFocus Context triple: [Dow Corning Corporation, hasTechnologyFocus, silicone chemistry]
-
A.
hasProgrammingFocus
Indicates that something is centered on, specialized in, or primarily concerned with programming.
-
B.
hasAdvancedTechnologySector
Indicates that an entity possesses or includes a developed sector focused on advanced or high-tech industries, products, or services.
-
C.
associatedWithTechnology
Indicates a relationship where an entity is connected to, involved with, or utilizes a particular technology.
-
D.
technologyPioneered
Indicates that an entity was the first or among the first to develop, introduce, or significantly advance a particular technology.
-
E.
technologyField
chosen
Indicates the area or domain of technology in which an entity is involved, specialized, or categorized.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:03 p.m.