Triple
T2114995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A44 |
E42589
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Leominster |
E209074
|
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: Leominster | Statement: [A44, connects, Leominster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leominster Context triple: [A44, connects, Leominster]
-
A.
Leominster
chosen
Leominster is a historic market town in Herefordshire, England, known for its medieval architecture and agricultural heritage.
-
B.
Leominster, Massachusetts
Leominster, Massachusetts is a small city in north-central Massachusetts known historically for its plastics industry and as the birthplace of the modern plastic comb.
-
C.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
D.
Springfield, Maine
Springfield, Maine is a small rural town located in Penobscot County in eastern Maine, known for its forested landscape and quiet, sparsely populated setting.
-
E.
Thomaston, Maine
Thomaston, Maine is a small coastal town in Knox County known for its historic architecture, shipbuilding heritage, and association with Revolutionary War general Henry Knox.
- 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_69a8871040f08190aac2e2d0ab6b47ad |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0724e08190a0a4210d86261d6d |
completed | March 7, 2026, 5:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3b13d9c8190b059d5c01518cf54 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:43 p.m.