Triple
T7079638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Downtown Chicago |
E164916
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | River North |
E72349
|
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: River North | Statement: [Downtown Chicago, hasPart, River North]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: River North Context triple: [Downtown Chicago, hasPart, River North]
-
A.
River North, Chicago
chosen
River North, Chicago is a vibrant downtown neighborhood known for its art galleries, nightlife, dining scene, and converted warehouse lofts just north of the Loop.
-
B.
River West
River West is a Chicago neighborhood known for its mix of converted industrial spaces, modern residential developments, and proximity to downtown and the Chicago River.
-
C.
West Loop
West Loop is a trendy Chicago neighborhood known for its transformed industrial warehouses, vibrant dining scene, and proximity to the Fulton Market District.
-
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.
Wicker Park
Wicker Park is a trendy Chicago neighborhood known for its vibrant arts scene, nightlife, and eclectic mix of boutiques, restaurants, and music venues.
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4f063488190b9e1c614a9294bd1 |
completed | March 27, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7947294d4819094d7cfb34efde915 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:40 p.m.