Triple
T17877190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Elba, New York |
E446984
|
entity |
| Predicate | hasLocalPlanningFocus |
P79132
|
FINISHED |
| Object | agricultural land preservation |
—
|
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: agricultural land preservation | Statement: [Town of Elba, New York, hasLocalPlanningFocus, agricultural land preservation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalPlanningFocus Context triple: [Town of Elba, New York, hasLocalPlanningFocus, agricultural land preservation]
-
A.
hasLocationFocus
Indicates that the primary emphasis or relevance of something is centered on a specific location or place.
-
B.
hasPlanningFunction
Indicates that an entity is responsible for or involved in planning, organizing, or determining future actions or strategies.
-
C.
hasFutureMissionPlanned
Indicates that an entity has a mission or task scheduled to occur at a future time.
-
D.
hasTransitFocus
Indicates that something is oriented toward, prioritizes, or is primarily concerned with transit or transportation services.
-
E.
hasPlanningContext
chosen
Indicates that an entity is associated with a specific planning-related situation, scope, or set of conditions that frame how it should be interpreted or used.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa6d24081908212e10d07c85a2b |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:18 a.m.