Triple
T1971495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dahlonega, Georgia |
E42810
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Gold City
Gold City is a nickname for Dahlonega, Georgia, a historic town famed for its early 19th-century gold rush and mining heritage.
|
E220228
|
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: Gold City | Statement: [Dahlonega, Georgia, nickname, Gold City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gold City Context triple: [Dahlonega, Georgia, nickname, Gold City]
-
A.
Gold Point
Gold Point is a historic Nevada mining ghost town known for its preserved old buildings and Wild West heritage.
-
B.
Golden City
Golden City is a poetic nickname for Prague, highlighting the city's historic skyline of gilded spires and sunlit architecture.
-
C.
Golden City
Golden City is a small rural town in Barton County, southwestern Missouri, known for its agricultural surroundings and tight-knit community.
-
D.
Golden City
Golden City is the popular nickname for Jaisalmer, a historic sandstone city in the Thar Desert of Rajasthan, India, famed for its golden-hued fort and architecture.
-
E.
Silver City
Silver City is the nickname of Meriden, Connecticut, historically known for its prominent silver manufacturing industry.
- 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: Gold City Triple: [Dahlonega, Georgia, nickname, Gold City]
Generated description
Gold City is a nickname for Dahlonega, Georgia, a historic town famed for its early 19th-century gold rush and mining heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gold City Target entity description: Gold City is a nickname for Dahlonega, Georgia, a historic town famed for its early 19th-century gold rush and mining heritage.
-
A.
Gold Point
Gold Point is a historic Nevada mining ghost town known for its preserved old buildings and Wild West heritage.
-
B.
Golden City
Golden City is a poetic nickname for Prague, highlighting the city's historic skyline of gilded spires and sunlit architecture.
-
C.
Golden City
Golden City is a small rural town in Barton County, southwestern Missouri, known for its agricultural surroundings and tight-knit community.
-
D.
Golden City
Golden City is the popular nickname for Jaisalmer, a historic sandstone city in the Thar Desert of Rajasthan, India, famed for its golden-hued fort and architecture.
-
E.
Silver City
Silver City is the nickname of Meriden, Connecticut, historically known for its prominent silver manufacturing industry.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb3d2836c8190a35cb6d8e2dd4bdf |
completed | March 7, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbdb5d7c8190ab3e7c368041c641 |
completed | March 8, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69adfcae8a348190aa5688d0d183c323 |
completed | March 8, 2026, 10:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adfd713c4081908a2fae2fada76dae |
completed | March 8, 2026, 10:51 p.m. |
Created at: March 4, 2026, 7:36 p.m.