Triple
T15862933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Wood |
E384635
|
entity |
| Predicate | hasPatentsIn |
P28530
|
FINISHED |
| Object | digital video recording |
—
|
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: digital video recording | Statement: [Anthony Wood, hasPatentsIn, digital video recording]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatentsIn Context triple: [Anthony Wood, hasPatentsIn, digital video recording]
-
A.
hasPatentPortfolioIn
chosen
Indicates that an entity holds or manages one or more patents within a specified jurisdiction, region, or technical domain.
-
B.
hasPatentGrant
Indicates that a patent grant exists conferring legal protection or rights to an entity for a specific invention or intellectual property.
-
C.
hasInventionProperty
Indicates that an entity possesses a specific characteristic, attribute, or quality related to an invention.
-
D.
numberOfPatents
Indicates the count of patents associated with a given entity.
-
E.
patentIn
Indicates that one entity holds or is associated with a patent located, filed, or registered in a particular jurisdiction, organization, or context represented by the other 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:50 a.m.