Triple
T15204453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llano County |
E363353
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Blanco County |
E361293
|
NE 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: Blanco County | Statement: [Llano County, borders, Blanco County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blanco County Context triple: [Llano County, borders, Blanco County]
-
A.
Blanco County
chosen
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.
-
B.
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.
-
C.
Mitchell County
Mitchell County is a rural county in west-central Texas known for its ranching, wind energy production, and the city of Colorado City as its county seat.
-
D.
Mitchell County
Mitchell County is a rural county in northern Iowa known for its small farming communities and agricultural landscape.
-
E.
Llano County
Llano County is a rural county in central Texas known for its scenic Hill Country landscapes, granite outcrops, and outdoor recreation around lakes and rivers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b693a48190a6230b7b52bc8cd3 |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa11f77788190866e0820d33af588 |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 3:11 a.m.