Triple
T8978865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 121 |
E214468
|
entity |
| Predicate | connectsTownsIn |
P83783
|
FINISHED |
| Object | western part of Maine |
—
|
LITERAL 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: western part of Maine | Statement: [Maine State Route 121, connectsTownsIn, western part of Maine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsTownsIn Context triple: [Maine State Route 121, connectsTownsIn, western part of Maine]
-
A.
connectsMunicipalities
chosen
Indicates a relationship where one entity serves as a link or route that joins two or more municipalities.
-
B.
connectsIslands
Indicates a relationship where something (such as a structure, route, or link) joins or provides passage between two or more islands.
-
C.
connectsCountyTown
Indicates a relationship where a county is linked or associated with a town, typically signifying that the town lies within or is administered by that county.
-
D.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
E.
connectsCityIndirectly
Indicates that one location is linked to a city through one or more intermediate locations or routes, rather than by a direct connection.
- F. None of above.
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_69ca839ea8b88190922c6a326ffcc0d3 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67a4b3e88190b778a9b5589cab6d |
completed | April 1, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed9a2d48190ad11381078e823b7 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:03 p.m.