Triple
T10912130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wyoming Territory |
E257726
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Weston County
Weston County is a rural county in northeastern Wyoming known for its ranching, coal mining, and forested landscapes near the Black Hills.
|
E908264
|
NE FINISHED |
How this triple was built (4 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: Weston County | Statement: [Wyoming Territory, hasPart, Weston County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weston County Context triple: [Wyoming Territory, hasPart, Weston County]
-
A.
Mayes County
Mayes County is a county in northeastern Oklahoma known for its mix of small towns, agricultural areas, and recreational lakes.
-
B.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
C.
Blanco County
Blanco County is a rural county in central Texas known for its scenic Hill Country landscapes, small towns, and outdoor recreation along the Blanco River.
-
D.
Greenwood County
Greenwood County is a county in western South Carolina known for its mix of small-city life, manufacturing, and agricultural communities centered around the city of Greenwood.
-
E.
Yoakum County
Yoakum County is a rural county in western Texas known for its agriculture and oil production.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Weston County Triple: [Wyoming Territory, hasPart, Weston County]
Generated description
Weston County is a rural county in northeastern Wyoming known for its ranching, coal mining, and forested landscapes near the Black Hills.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weston County Target entity description: Weston County is a rural county in northeastern Wyoming known for its ranching, coal mining, and forested landscapes near the Black Hills.
-
A.
Mayes County
Mayes County is a county in northeastern Oklahoma known for its mix of small towns, agricultural areas, and recreational lakes.
-
B.
Mason County
Mason County is a county in western Washington State known for its forests, waterways, and location along the southern reaches of Puget Sound.
-
C.
Blanco County
Blanco County is a rural county in central Texas known for its scenic Hill Country landscapes, small towns, and outdoor recreation along the Blanco River.
-
D.
Greenwood County
Greenwood County is a county in western South Carolina known for its mix of small-city life, manufacturing, and agricultural communities centered around the city of Greenwood.
-
E.
Yoakum County
Yoakum County is a rural county in western Texas known for its agriculture and oil production.
- F. None of above. chosen
Provenance (5 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770723df08190bedfdc94d998f969 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e46283f41c8190ac3e1f196c5e4ca0 |
completed | April 19, 2026, 5:05 a.m. |
| NEDg | Description generation | batch_69e46c3448348190b2c062d21771066d |
completed | April 19, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e46dadbc5c8190b41279a05731dc95 |
completed | April 19, 2026, 5:52 a.m. |
Created at: April 8, 2026, 9:22 p.m.