Triple
T843761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oregon Coast |
E18232
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Seaside
Seaside is a popular resort city on the northern Oregon Coast known for its sandy beaches, historic promenade, and family-friendly attractions.
|
E104355
|
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: Seaside | Statement: [Oregon Coast, hasCity, Seaside]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seaside Context triple: [Oregon Coast, hasCity, Seaside]
-
A.
The Bay
The Bay is a major Canadian department store chain offering a wide range of fashion, home goods, and accessories.
-
B.
Stage Harbor
Stage Harbor is a scenic natural harbor in Chatham, Massachusetts, known for its sheltered waters, boating, and classic Cape Cod coastal views.
-
C.
Sunset Beach
Sunset Beach is a famous North Shore Oahu surf spot known for its massive winter waves and picturesque sunsets.
-
D.
Riverhead
Riverhead is a town on the eastern end of Long Island in New York, known as the county seat of Suffolk County and a gateway to the North Fork wine region.
-
E.
Harborland
Harborland is a popular waterfront shopping and entertainment district in Kobe, Japan, known for its modern malls, restaurants, and scenic harbor views.
- 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: Seaside Triple: [Oregon Coast, hasCity, Seaside]
Generated description
Seaside is a popular resort city on the northern Oregon Coast known for its sandy beaches, historic promenade, and family-friendly attractions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seaside Target entity description: Seaside is a popular resort city on the northern Oregon Coast known for its sandy beaches, historic promenade, and family-friendly attractions.
-
A.
The Bay
The Bay is a major Canadian department store chain offering a wide range of fashion, home goods, and accessories.
-
B.
Stage Harbor
Stage Harbor is a scenic natural harbor in Chatham, Massachusetts, known for its sheltered waters, boating, and classic Cape Cod coastal views.
-
C.
Sunset Beach
Sunset Beach is a famous North Shore Oahu surf spot known for its massive winter waves and picturesque sunsets.
-
D.
Riverhead
Riverhead is a town on the eastern end of Long Island in New York, known as the county seat of Suffolk County and a gateway to the North Fork wine region.
-
E.
Harborland
Harborland is a popular waterfront shopping and entertainment district in Kobe, Japan, known for its modern malls, restaurants, and scenic harbor views.
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac07fedc8190ab05595f25c1792f |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b8472f188190b470893c76b20ccf |
completed | March 4, 2026, 4:42 a.m. |
| NEDg | Description generation | batch_69a7bc1acf708190aa86cd5eca101966 |
completed | March 4, 2026, 4:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7bc96dd2881909310147292b99023 |
completed | March 4, 2026, 5:01 a.m. |
Created at: March 1, 2026, 7:38 p.m.