Triple
T10566801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 137 |
E249370
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Knox, Maine |
E848893
|
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: Knox, Maine | Statement: [Maine State Route 137, connects, Knox, Maine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knox, Maine Context triple: [Maine State Route 137, connects, Knox, Maine]
-
A.
Knox, Maine
chosen
Knox, Maine is a small rural town located in Waldo County in the state of Maine, United States.
-
B.
Winslow, Maine
Winslow, Maine is a small town in Kennebec County known for its rural character, historic sites, and location along the Kennebec River in central Maine.
-
C.
Waterford, Maine
Waterford, Maine is a small rural town in Oxford County known for its lakes, forests, and traditional New England village character.
-
D.
Thorndike, Maine
Thorndike, Maine is a small rural town located in Waldo County in the central part of the state.
-
E.
Lovell, Maine
Lovell, Maine is a small rural town in Oxford County known for its scenic lakes and mountains in western Maine.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5272ef5848190b76d671ea2d26314 |
completed | April 7, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a5a733c819090a6710ab990c38d |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 6, 2026, 12:36 p.m.