Triple
T90094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence |
E1810
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Methuen |
E203201
|
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: Methuen | Statement: [Lawrence, borderedBy, Methuen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Methuen Context triple: [Lawrence, borderedBy, Methuen]
-
A.
Fitchburg
Fitchburg is a small city in north-central Massachusetts known for its industrial history, hilly terrain, and role as a regional rail hub.
-
B.
Leominster
Leominster is a historic market town in Herefordshire, England, known for its medieval architecture and agricultural heritage.
-
C.
Andover
Andover is a town in Hampshire, England, known in part for its role as a major administrative and logistical center for the British Army.
-
D.
Andover
chosen
Andover is a town in northeastern Massachusetts known for its historic New England character, strong public schools, and institutions like Phillips Academy.
-
E.
Swampscott
Swampscott is a coastal town in northeastern Massachusetts known for its residential character and seaside location north of Boston.
- 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_69a24d1a97dc819094e6c021fe9b05a7 |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a383e3575c8190932dcdc25503d06e |
completed | March 1, 2026, 12:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaaaad508190992c7b50e9397450 |
completed | March 8, 2026, 9:31 p.m. |
Created at: Feb. 28, 2026, 2:07 a.m.