Triple
T21299758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dawson County, Texas |
E525023
|
entity |
| Predicate | isDrylandFarmingRegion |
P143644
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Dawson County, Texas, isDrylandFarmingRegion, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDrylandFarmingRegion Context triple: [Dawson County, Texas, isDrylandFarmingRegion, yes]
-
A.
locatedInAgriculturalRegion
Indicates that an entity is situated within a region primarily characterized by agricultural activities or land use.
-
B.
hasIrrigatedAgriculture
Indicates that an entity engages in or possesses agricultural activities that are supported or sustained by artificial irrigation systems.
-
C.
connectsToAgriculturalRegion
Indicates a relationship where something is linked or associated with an agricultural region, such as through proximity, infrastructure, or functional interaction.
-
D.
isRuralRegion
Indicates that a region is classified as rural, typically characterized by low population density and limited urban development.
-
E.
isCultivated
Indicates that an entity is intentionally grown, managed, or maintained by humans rather than occurring or developing naturally without human intervention.
- F. None of above. chosen
Provenance (4 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385b1c548190b940ded0163ee3ca |
completed | April 21, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e6190163448190a2404b396215c686 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 16, 2026, 4:05 p.m.