Triple
T19427214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Independence Township, Beaver County, Pennsylvania |
E486009
|
entity |
| Predicate | hasFarmland |
P121969
|
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: [Independence Township, Beaver County, Pennsylvania, hasFarmland, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFarmland Context triple: [Independence Township, Beaver County, Pennsylvania, hasFarmland, true]
-
A.
hasFarm
Indicates that one entity owns, operates, or is responsible for a farm associated with another entity.
-
B.
hasAgriculturalCharacter
Indicates that something possesses qualities, features, or uses typical of agriculture or farming activities.
-
C.
hasNotableFarm
Indicates that an entity possesses or is associated with a farm that is considered notable or significant in some recognized way.
-
D.
hasAgriculturalProduction
Indicates that an entity engages in or is characterized by the production of agricultural goods such as crops or livestock.
-
E.
hasFertileLand
chosen
Indicates that one entity possesses or contains land that is capable of supporting abundant plant growth or agricultural production.
- 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63219f27481909fe686209defc971 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.