Triple
T7297830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seaside |
E164568
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object |
Sand City
Sand City is a small coastal city in Monterey County, California, known for its beaches, sand dunes, and outlet shopping.
|
E655315
|
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: Sand City | Statement: [Seaside, adjacentTo, Sand City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sand City Context triple: [Seaside, adjacentTo, Sand City]
-
A.
Stone City
Stone City is an ancient walled city and historic fortification area that forms part of the old core of Nanjing, China.
-
B.
River City
River City is a common nickname and place name in the United States, often referring to cities situated along major rivers and popularized in American culture and media.
-
C.
River City
River City is a popular nickname for Richmond, Virginia, highlighting the city's location along the James River and its historic riverfront character.
-
D.
River City
River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
-
E.
River City
River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
- 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: Sand City Triple: [Seaside, adjacentTo, Sand City]
Generated description
Sand City is a small coastal city in Monterey County, California, known for its beaches, sand dunes, and outlet shopping.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sand City Target entity description: Sand City is a small coastal city in Monterey County, California, known for its beaches, sand dunes, and outlet shopping.
-
A.
Stone City
Stone City is an ancient walled city and historic fortification area that forms part of the old core of Nanjing, China.
-
B.
River City
River City is a common nickname and place name in the United States, often referring to cities situated along major rivers and popularized in American culture and media.
-
C.
River City
River City is a popular nickname for Richmond, Virginia, highlighting the city's location along the James River and its historic riverfront character.
-
D.
River City
River City is a popular nickname for Sacramento, California, highlighting the city’s close connection to the nearby American and Sacramento Rivers.
-
E.
River City
River City is a popular nickname for Wuhan, a major central Chinese metropolis known for its location at the confluence of the Yangtze and Han rivers.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb8f83c881909e8eae85410f9659 |
completed | March 27, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7e54c25c88190891311b72f242e86 |
completed | March 28, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_69c7e5ef420081908026576aaba34b11 |
completed | March 28, 2026, 2:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7e67d64748190a4b5765a06413fd6 |
completed | March 28, 2026, 2:32 p.m. |
Created at: March 27, 2026, 3 p.m.