Triple
T34424110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Seeds |
E883623
|
entity |
| Predicate | includesNonAgriculturalContent |
P70649
|
FINISHED |
| Object | laws of blessings |
—
|
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: laws of blessings | Statement: [Order of Seeds, includesNonAgriculturalContent, laws of blessings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesNonAgriculturalContent Context triple: [Order of Seeds, includesNonAgriculturalContent, laws of blessings]
-
A.
nonResidential
Indicates that something is not intended or used for residential or living purposes.
-
B.
doesNotPrimarilyContain
chosen
Indicates that one entity does not have another entity as its main or predominant component, element, or content.
-
C.
landUseIncludes
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
D.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
E.
representsAgriculture
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation to 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_69f349c3dd2c819092cc9e64809f4a42 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2 a.m.