Triple
T868610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO 9660 |
E18760
|
entity |
| Predicate | extension |
P11869
|
FINISHED |
| Object | Joliet |
E71725
|
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: Joliet | Statement: [ISO 9660, extension, Joliet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joliet Context triple: [ISO 9660, extension, Joliet]
-
A.
Joliet, Illinois
chosen
Joliet, Illinois is a mid-sized city southwest of Chicago known for its historic prison, riverfront, and role as a regional industrial and transportation hub.
-
B.
Peoria
Peoria is a suburban city in the Phoenix metropolitan area of central Arizona, known for its rapid growth, residential communities, and recreational amenities.
-
C.
Calumet City, Illinois
Calumet City, Illinois is a suburban city in the Chicago metropolitan area known historically for its industrial roots and proximity to the Indiana state line.
-
D.
Mundelein, Illinois
Mundelein, Illinois is a suburban village in Lake County known for its residential communities, parks, and commuter access to the Chicago metropolitan area.
-
E.
Waukegan, Illinois
Waukegan, Illinois is an industrial port city on Lake Michigan in Lake County that serves as a northern suburb within the greater Chicago metropolitan area.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac7f98908190883f71049092c7c8 |
completed | March 1, 2026, 9:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01ccc410c819094800b656937b61e |
completed | March 10, 2026, 1:29 p.m. |
Created at: March 1, 2026, 7:39 p.m.