Triple
T26090869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kergunyah |
E658116
|
entity |
| Predicate | hasFarmingCommunity |
P85413
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kergunyah, hasFarmingCommunity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFarmingCommunity Context triple: [Kergunyah, hasFarmingCommunity, true]
-
A.
hasAgriculturalCommunities
chosen
Indicates that certain groups or settlements engage in organized farming and related agricultural activities within a given area or context.
-
B.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
C.
hasNotableFarm
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
-
D.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
E.
hasRuralArea
Indicates that an entity includes, is associated with, or contains a countryside or sparsely populated geographic area.
- 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_69ee5bbfc4d08190a1b206d0ac3a1e8d |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 26, 2026, 7:47 p.m.