Triple
T19727226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The King’s Men |
E473758
|
entity |
| Predicate | receivedRoyalPatentInYear |
P1928
|
FINISHED |
| Object | 1603 |
—
|
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: 1603 | Statement: [The King’s Men, receivedRoyalPatentInYear, 1603]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivedRoyalPatentInYear Context triple: [The King’s Men, receivedRoyalPatentInYear, 1603]
-
A.
grantedRoyalPatentBy
Indicates that an entity has been formally given a royal patent by a specified royal authority or monarch.
-
B.
hasPatentGrant
Indicates that a patent grant exists conferring legal protection or rights to an entity for a specific invention or intellectual property.
-
C.
grantedPatentAs
Indicates that a patent has been officially granted to an entity in a specified role or capacity.
-
D.
patentDate
chosen
Indicates the date on which a patent was officially granted or registered.
-
E.
yearOfPublicDisclosure
Indicates the calendar year in which information, an invention, or other subject matter was first publicly disclosed.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f95d5c8190858ba414ff3e95a8 |
completed | April 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.