Triple
T30644589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edison incandescent lamps |
E780085
|
entity |
| Predicate | hasPatentNumber |
P35427
|
FINISHED |
| Object | US223898 |
—
|
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: US223898 | Statement: [Edison incandescent lamps, hasPatentNumber, US223898]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatentNumber Context triple: [Edison incandescent lamps, hasPatentNumber, US223898]
-
A.
patentNumber
chosen
Indicates that a specific patent is identified or referenced by a particular patent number.
-
B.
hasPatentGrant
Indicates that a patent grant exists conferring legal protection or rights to an entity for a specific invention or intellectual property.
-
C.
numberOfPatents
Indicates the count of patents associated with a given entity.
-
D.
hasNoPatentGrant
Indicates that no patent grant has been issued or is associated with the referenced entity or subject.
-
E.
heldPatentOn
Indicates that one entity legally possessed the rights to a specific patent covering an invention, process, or design.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe5d58c3e48190910aa3c23485e2c4 |
completed | May 8, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69fe5c92090c8190bcfa412c0a3619df |
completed | May 8, 2026, 9:58 p.m. |
Created at: April 29, 2026, 8:29 p.m.