Triple
T2374028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ann Arbor |
E46153
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
Tree Town
Tree Town is a leafy nickname for Ann Arbor, Michigan, highlighting the city's abundant trees and green spaces.
|
E260068
|
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: Tree Town | Statement: [Ann Arbor, hasNickname, Tree Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tree Town Context triple: [Ann Arbor, hasNickname, Tree Town]
-
A.
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.
-
B.
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.
-
C.
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.
-
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.
Gate City
Gate City is a commonly used nickname for Greensboro, North Carolina, reflecting its historic role as a major transportation and commercial hub.
- 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: Tree Town Triple: [Ann Arbor, hasNickname, Tree Town]
Generated description
Tree Town is a leafy nickname for Ann Arbor, Michigan, highlighting the city's abundant trees and green spaces.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tree Town Target entity description: Tree Town is a leafy nickname for Ann Arbor, Michigan, highlighting the city's abundant trees and green spaces.
-
A.
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.
-
B.
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.
-
C.
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.
-
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.
Gate City
Gate City is a commonly used nickname for Greensboro, North Carolina, reflecting its historic role as a major transportation and commercial hub.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc791c4688190a4b8f0e540e84eb4 |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea8a8c2b88190a18dbf35d745958f |
completed | March 9, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_69aea92cc66c81909a46b83200960fe2 |
completed | March 9, 2026, 11:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69aea9b8dff08190a09f0c965dfd6738 |
completed | March 9, 2026, 11:06 a.m. |
Created at: March 4, 2026, 7:56 p.m.