Triple
T4158310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pomo |
E91469
|
entity |
| Predicate | traditionalTerritory |
P1103
|
FINISHED |
| Object | Lake County |
E146448
|
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: Lake County | Statement: [Pomo, traditionalTerritory, Lake County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake County Context triple: [Pomo, traditionalTerritory, Lake County]
-
A.
Lake County
Lake County is a county in northwestern Indiana known for its industrial cities, including Gary, and its location along the southern shore of Lake Michigan.
-
B.
Lake County
chosen
Lake County is a rural county in Northern California known for Clear Lake, extensive vineyards and wineries, and its mountainous, volcanic landscape.
-
C.
Lake County
Lake County is a county in northeastern Minnesota known for its North Shore scenery along Lake Superior and extensive forests and lakes.
-
D.
Martin County
Martin County is a coastal county on Florida’s Atlantic Treasure Coast known for its beaches, waterways, and mix of small cities and natural preserves.
-
E.
Martin County
Martin County is a sparsely populated rural county in western Texas known primarily for its agriculture and oil production.
- 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_69aed9626ebc8190a39de631788bea3e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02919134819080ef36598bb4ca32 |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b65f1b86908190965342d8da0ff545 |
completed | March 15, 2026, 7:26 a.m. |
Created at: March 9, 2026, 3:44 p.m.