Triple
T10705945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maine State Route 139 |
E252404
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SR 139 |
E583777
|
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: SR 139 | Statement: [Maine State Route 139, abbreviation, SR 139]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SR 139 Context triple: [Maine State Route 139, abbreviation, SR 139]
-
A.
SR 139
chosen
SR 139 is a state highway in Alabama that serves as a regional connector route between local communities.
-
B.
SR 119
SR 119 is a state highway in Alabama that serves as a regional connector route through several suburban and rural communities.
-
C.
SR 131
SR 131 is a state highway in Maine that runs through Knox and Waldo counties, connecting several coastal and inland communities.
-
D.
SR 132
SR 132 is a state highway in Maine that connects several small communities and links with other major regional routes.
-
E.
SR 113
SR 113 is a state highway in northern Ohio that runs east–west through several counties, connecting rural areas with small towns and cities.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddfbed48190810bb3faee473fde |
completed | April 9, 2026, 1:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998fe56dc8190ae0c987b28ec6206 |
completed | April 11, 2026, 12:42 a.m. |
Created at: April 8, 2026, 9:12 p.m.