Triple
T17964476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago–Naperville–Elgin, IL–IN–WI Metropolitan Statistical Area |
E449165
|
entity |
| Predicate | containsStatePortion |
P45758
|
FINISHED |
| Object | northeastern Illinois |
—
|
LITERAL 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: northeastern Illinois | Statement: [Chicago–Naperville–Elgin, IL–IN–WI Metropolitan Statistical Area, containsStatePortion, northeastern Illinois]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsStatePortion Context triple: [Chicago–Naperville–Elgin, IL–IN–WI Metropolitan Statistical Area, containsStatePortion, northeastern Illinois]
-
A.
hasStatePortionIn
Indicates that a state has a geographic portion or area located within the boundaries of another region or entity.
-
B.
containsPortionOf
chosen
Indicates that one entity includes or holds a part, segment, or fraction of another entity.
-
C.
includesPort
Indicates that one entity contains, encompasses, or has as part of it a specific port or set of ports.
-
D.
hasPortionDesignatedAs
Indicates that one entity has a specific part or segment that is explicitly identified or designated as another entity.
-
E.
hasMissingPortions
Indicates that an entity is incomplete because some of its expected parts or sections are absent.
- F. None of above.
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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b136e4088190ac97fd92dc84a4b9 |
completed | April 19, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69e3f8fa62688190a5d5c361ab896256 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:22 a.m.