Triple
T15204451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llano County |
E363353
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Mason County |
E994977
|
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: Mason County | Statement: [Llano County, borders, Mason County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mason County Context triple: [Llano County, borders, Mason County]
-
A.
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.
-
B.
Mason County
chosen
Mason County is a rural county in central Texas known for its ranching, hunting, and the historic town of Mason.
-
C.
Grant County
Grant County is a county in east-central Indiana known for its small towns, agricultural landscape, and historical ties to figures like James Dean.
-
D.
Grant County
Grant County is a county in central Washington State known for its agricultural production, reservoirs, and outdoor recreation areas.
-
E.
Grant County
Grant County is a rural county in eastern West Virginia known for its mountainous terrain, outdoor recreation areas, and small communities.
- 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_69ff8757325c8190ad97f50368862ca5 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 3:11 a.m.