Triple
T2345763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billings |
E45126
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Magic City
Magic City is the nickname of Billings, Montana, reflecting its rapid growth from a small railroad town into the state’s largest city.
|
E257560
|
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: Magic City | Statement: [Billings, nickname, Magic City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magic City Context triple: [Billings, nickname, Magic City]
-
A.
The Magic City
The Magic City is a nickname for Birmingham, Alabama, highlighting its rapid growth during the late 19th and early 20th centuries as an industrial and economic center.
-
B.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
-
C.
Collar City
Collar City is the nickname for Troy, New York, historically known as a major center of shirt-collar and textile manufacturing.
-
D.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
E.
Rocket City
Rocket City is the nickname for Huntsville, Alabama, a city renowned for its pivotal role in U.S. space exploration and rocket development.
- 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: Magic City Triple: [Billings, nickname, Magic City]
Generated description
Magic City is the nickname of Billings, Montana, reflecting its rapid growth from a small railroad town into the state’s largest city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magic City Target entity description: Magic City is the nickname of Billings, Montana, reflecting its rapid growth from a small railroad town into the state’s largest city.
-
A.
The Magic City
The Magic City is a nickname for Birmingham, Alabama, highlighting its rapid growth during the late 19th and early 20th centuries as an industrial and economic center.
-
B.
Winter City
Winter City is the popular nickname for Östersund, a Swedish town renowned for its cold climate and strong winter sports culture.
-
C.
Collar City
Collar City is the nickname for Troy, New York, historically known as a major center of shirt-collar and textile manufacturing.
-
D.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
E.
Rocket City
Rocket City is the nickname for Huntsville, Alabama, a city renowned for its pivotal role in U.S. space exploration and rocket development.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6c7cb9481909405aeb503f804ae |
completed | March 7, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9628059481909c96a7661bc87a73 |
completed | March 9, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ae9727a28881909eebc67189dfc856 |
completed | March 9, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae9795cf048190bc7a01ef86c12138 |
completed | March 9, 2026, 9:49 a.m. |
Created at: March 4, 2026, 7:52 p.m.