Triple
T30281613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guion Farm Access Area |
E770107
|
entity |
| Predicate | hasSecondarySetting |
P146042
|
FINISHED |
| Object | pasture and fields |
—
|
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: pasture and fields | Statement: [Guion Farm Access Area, hasSecondarySetting, pasture and fields]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondarySetting Context triple: [Guion Farm Access Area, hasSecondarySetting, pasture and fields]
-
A.
hasSecondary
Indicates that an entity is associated with an additional or subordinate counterpart beyond its primary one.
-
B.
hasSecondaryUsage
Indicates that an entity is associated with an additional, non-primary function or purpose beyond its main intended use.
-
C.
hasSecondaryComponent
chosen
Indicates that an entity includes or is associated with an additional, subordinate component beyond its primary one.
-
D.
hasSecondarySee
Indicates that an entity has an additional, secondary “see also” reference or cross-link to another related entity.
-
E.
hasSecondaryUser
Indicates that an entity is associated with an additional, non-primary user who also has access to or control over it.
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe991bca608190b524e419642f4243 |
completed | May 9, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69fe979fc1c4819091fc48d63ea12063 |
completed | May 9, 2026, 2:10 a.m. |
Created at: April 29, 2026, 7:45 p.m.