Triple
T9638413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 130 |
E232994
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object |
Lincoln County
Lincoln County is a coastal county in Maine known for its historic towns, maritime heritage, and scenic Midcoast landscapes.
|
E818979
|
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: Lincoln County | Statement: [Maine State Route 130, county, Lincoln County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lincoln County Context triple: [Maine State Route 130, county, Lincoln County]
-
A.
Lincoln County
Lincoln County is a county in North Carolina that forms part of the greater Charlotte metropolitan region.
-
B.
Lincoln County
Lincoln County is a sparsely populated rural county in eastern Colorado known for its agricultural economy and small towns on the High Plains.
-
C.
Lincoln County
Lincoln County is a county-level jurisdiction in the U.S. state of Mississippi, with Brookhaven as its county seat.
-
D.
Lincoln County
Lincoln County is a county in central Oklahoma known for its mix of small towns, agricultural land, and proximity to the Oklahoma City metropolitan area.
-
E.
Lincoln County
Lincoln County is a coastal county in western Oregon known for its scenic Pacific shoreline, lighthouses, and tourism-centered communities.
- 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: Lincoln County Triple: [Maine State Route 130, county, Lincoln County]
Generated description
Lincoln County is a coastal county in Maine known for its historic towns, maritime heritage, and scenic Midcoast landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lincoln County Target entity description: Lincoln County is a coastal county in Maine known for its historic towns, maritime heritage, and scenic Midcoast landscapes.
-
A.
Lincoln County
Lincoln County is a coastal county in western Oregon known for its scenic Pacific shoreline, lighthouses, and tourism-centered communities.
-
B.
Lincoln County
Lincoln County is a sparsely populated agricultural county in eastern Washington State, known for its wheat farming and rural landscapes.
-
C.
Lincoln County
Lincoln County is a rural county in northern Idaho known for its small communities and natural landscapes.
-
D.
Lincoln County
Lincoln County is a rural county in south-central Idaho, known for its agricultural landscape and proximity to the Magic Valley region.
-
E.
Lincoln County
Lincoln County is a county in central Oklahoma known for its mix of small towns, agricultural land, and proximity to the Oklahoma City metropolitan area.
- 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_69ca848a5a908190aad251f4137b0c3a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b51b08081908e30744607b28953 |
completed | April 1, 2026, 10:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1af6abb008190860e4742656baa97 |
completed | April 5, 2026, 12:40 a.m. |
| NEDg | Description generation | batch_69d1b167f3a88190a9ddf65f8035f945 |
completed | April 5, 2026, 12:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b1cdc91481908e98c4d5cdec785b |
completed | April 5, 2026, 12:50 a.m. |
Created at: March 30, 2026, 8:11 p.m.