Triple
T1189410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nova Scotia |
E25322
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Lunenburg
Lunenburg is a historic coastal town in eastern Canada renowned for its colorful waterfront, shipbuilding heritage, and UNESCO World Heritage–listed Old Town.
|
E138370
|
NE FINISHED |
How this triple was built (4 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: Lunenburg | Statement: [Nova Scotia, contains, Lunenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lunenburg Context triple: [Nova Scotia, contains, Lunenburg]
-
A.
Lunenburg
Lunenburg is a small town in north-central Massachusetts known for its residential character and proximity to commuter rail service into the Boston area.
-
B.
Yarmouth
Yarmouth is a coastal town on Cape Cod in Massachusetts known for its beaches, historic villages, and tourism.
-
C.
Yarmouth
Yarmouth is a small historic port town and popular tourist destination on the western side of the Isle of Wight in England.
-
D.
Hampton
Hampton is a suburban town in the London Borough of Richmond upon Thames, England, situated on the north bank of the River Thames.
-
E.
Hampton
Hampton is an independent coastal city in southeastern Virginia known for its historic role in early American settlement and its location at the entrance to the Chesapeake Bay.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lunenburg Triple: [Nova Scotia, contains, Lunenburg]
Generated description
Lunenburg is a historic coastal town in eastern Canada renowned for its colorful waterfront, shipbuilding heritage, and UNESCO World Heritage–listed Old Town.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lunenburg Target entity description: Lunenburg is a historic coastal town in eastern Canada renowned for its colorful waterfront, shipbuilding heritage, and UNESCO World Heritage–listed Old Town.
-
A.
Lunenburg
Lunenburg is a small town in north-central Massachusetts known for its residential character and proximity to commuter rail service into the Boston area.
-
B.
Yarmouth
Yarmouth is a coastal town on Cape Cod in Massachusetts known for its beaches, historic villages, and tourism.
-
C.
Yarmouth
Yarmouth is a small historic port town and popular tourist destination on the western side of the Isle of Wight in England.
-
D.
Hampton
Hampton is a suburban town in the London Borough of Richmond upon Thames, England, situated on the north bank of the River Thames.
-
E.
Hampton
Hampton is an independent coastal city in southeastern Virginia known for its historic role in early American settlement and its location at the entrance to the Chesapeake Bay.
- F. None of above. chosen
Provenance (5 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_69a49427d98881908646d6c63b8cea1e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd57c3c481908bdca483fcaa3297 |
completed | March 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7f36371c8190a656463a9ae6402a |
completed | March 7, 2026, 7:40 p.m. |
| NEDg | Description generation | batch_69ac7f9a55dc819098204d53aac70ef3 |
completed | March 7, 2026, 7:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac80c3c6b08190a99119f5661c0157 |
completed | March 7, 2026, 7:47 p.m. |
Created at: March 1, 2026, 7:45 p.m.