Triple
T3501896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Printers Row |
E73987
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | South Loop |
E109326
|
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: South Loop | Statement: [Printers Row, near, South Loop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: South Loop Context triple: [Printers Row, near, South Loop]
-
A.
North Loop
North Loop is a trendy, revitalized warehouse district in downtown Minneapolis known for its upscale restaurants, boutiques, and vibrant nightlife.
-
B.
South Loop neighborhood
chosen
The South Loop neighborhood is a rapidly developing area just south of Chicago’s downtown, known for its mix of historic lofts, new high-rises, and proximity to major cultural and lakefront attractions.
-
C.
Logan Square
Logan Square is a notable public square and local landmark situated in the Hyde Park neighborhood of Boston, Massachusetts.
-
D.
Wicker Park
Wicker Park is a 2004 romantic psychological thriller film starring Josh Hartnett, known for its intricate plot about obsession, mistaken identity, and lost love.
-
E.
Chicago Loop
Chicago Loop is the central business district and historic downtown core of Chicago, known for its skyscrapers, theaters, parks, and major cultural attractions.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbef47988190b5b3fe2e452b9ac8 |
completed | March 8, 2026, 6:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bc25328819098f7744ee228d665 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:18 p.m.