Triple
T1288641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monmouthshire |
E27493
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Monmouth |
E28326
|
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: Monmouth | Statement: [Monmouthshire, containsSettlement, Monmouth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monmouth Context triple: [Monmouthshire, containsSettlement, Monmouth]
-
A.
Monmouth
chosen
Monmouth is a historic market town in Monmouthshire, Wales, known for its medieval architecture and position near the English border.
-
B.
Sussex County
Sussex County is a county in the southern part of the U.S. state of Delaware, known for its coastal resorts, agriculture, and historic towns.
-
C.
Essex County
Essex County is a southwestern Ontario region bordering Lake Erie that includes the southernmost point of mainland Canada and encompasses Point Pelee National Park.
-
D.
Essex County
Essex County is a historic coastal county in northeastern Massachusetts that includes cities such as Lynn, Salem, and Lawrence.
-
E.
Brunswick
Brunswick is a historic city in northern Germany known for its medieval heritage and as the birthplace of mathematician Carl Friedrich Gauss.
- 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_69a496d4ec448190ad653b2590c46711 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c0d38d7c81908941edda9cac5d6a |
completed | March 1, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc6209a388190b9f018b63120b28c |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:51 p.m.