Triple
T128601
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlanta |
E2602
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object | A-Town |
E15509
|
NE FINISHED |
How this triple was built (2 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: A-Town | Statement: [Atlanta, hasNickname, A-Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: A-Town Context triple: [Atlanta, hasNickname, A-Town]
-
A.
Chocolate City
Chocolate City is a popular nickname for Washington, D.C., highlighting its historically large and influential African American population and culture.
-
B.
Streeterville
Streeterville is a vibrant neighborhood on Chicago’s Near North Side known for its lakefront attractions, high-rise buildings, and major cultural and tourist destinations.
-
C.
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.
-
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.
Hotlanta
chosen
Hotlanta is a popular nickname for Atlanta, Georgia, highlighting the city's vibrant nightlife, music scene, and warm climate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25763ccf8819094e8dffb2ff98480 |
completed | Feb. 28, 2026, 2:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2b01814e88190a21f98527b8f9420 |
completed | Feb. 28, 2026, 9:06 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.