Triple
T845718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baltimore County |
E18272
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Dundalk |
E144735
|
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: Dundalk | Statement: [Baltimore County, contains, Dundalk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dundalk Context triple: [Baltimore County, contains, Dundalk]
-
A.
Dundalk
chosen
Dundalk is a large unincorporated community and suburb of Baltimore, Maryland, known for its residential neighborhoods and industrial history along the Patapsco River.
-
B.
Armagh
Armagh is a historic city in Northern Ireland renowned as the ecclesiastical capital of Ireland and a major center of Christian heritage linked to Saint Patrick.
-
C.
Waterford
Waterford is a small town and village in eastern New York State, known as the eastern terminus of the Erie Canal and its historic canal locks.
-
D.
Waterford
Waterford is a small incorporated city located in Stanislaus County in California’s Central Valley.
-
E.
Lisburn
Lisburn is a city in Northern Ireland known historically for its linen industry and located southwest of Belfast.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac0a91e48190b4349ae8bb67fd90 |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aca2caba8c81908ef693677acbd4cc |
completed | March 7, 2026, 10:12 p.m. |
Created at: March 1, 2026, 7:38 p.m.