Triple
T9250889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Porpoise |
E222319
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Kennebunkport |
E224549
|
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: Kennebunkport | Statement: [Cape Porpoise, partOf, Kennebunkport]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kennebunkport Context triple: [Cape Porpoise, partOf, Kennebunkport]
-
A.
Kennebunkport
chosen
Kennebunkport is a coastal resort town in southern Maine known for its historic charm, beaches, and long association with the Bush family.
-
B.
Kennebunk, Maine
Kennebunk, Maine is a coastal New England town known for its historic charm, beaches, and popular summer tourism.
-
C.
Camden Hills
Camden Hills is a scenic coastal mountain range and state park area in Maine known for its hiking trails and panoramic views of Penobscot Bay.
-
D.
North Haven
North Haven is a coastal town in New South Wales, Australia, known for its beaches and relaxed seaside lifestyle.
-
E.
Center Harbor
Center Harbor is a small New England town in New Hampshire known for its scenic location on the shores of Lake Winnipesaukee and Squam Lake.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f9ade48190ac8425a1c6f066b1 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0780650648190bc85452678268134 |
completed | April 4, 2026, 2:31 a.m. |
Created at: March 30, 2026, 7:31 p.m.