Triple
T20626617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Underground Atlanta |
E506834
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Five Points, Atlanta |
—
|
NE NERFINISHED |
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: Five Points, Atlanta | Statement: [Underground Atlanta, near, Five Points, Atlanta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Five Points, Atlanta Context triple: [Underground Atlanta, near, Five Points, Atlanta]
-
A.
Five Points, Atlanta
chosen
Five Points, Atlanta is the historic central hub and major transit and commercial crossroads of downtown Atlanta.
-
B.
Five Points
Five Points is the name of several small unincorporated communities and crossroads locations in the U.S. state of Michigan.
-
C.
Five Points
Five Points is a historic Denver neighborhood known as a longtime center of African American culture and jazz.
-
D.
Five Points
Five Points is a historic, bohemian neighborhood in Jacksonville, Florida, known for its eclectic mix of shops, restaurants, nightlife, and arts venues.
-
E.
Five Points, Manhattan
Five Points, Manhattan was a notorious 19th-century New York City neighborhood known for its extreme poverty, crime, and dense immigrant population.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe576c081909231dc0d7304b9a9 |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.