Triple
T15329903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Kane |
E366504
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object | Illinois |
E13723
|
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: Illinois | Statement: [Tom Kane, setIn, Illinois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Illinois Context triple: [Tom Kane, setIn, Illinois]
-
A.
Illinois
chosen
Illinois is a Midwestern U.S. state known for its major metropolis Chicago, diverse economy, and significant political and transportation influence.
-
B.
Illinois 47
Illinois 47 is a north–south state highway in Illinois that runs through both rural areas and growing suburban communities, serving as a key regional route.
-
C.
Como, Illinois
Como, Illinois is a small unincorporated community in Whiteside County that forms part of the Sterling Micropolitan Statistical Area.
-
D.
Illinois and Indiana
Illinois and Indiana are neighboring Midwestern U.S. states whose shared boundary is partly defined by the Ohio River.
-
E.
Indiana
Indiana is a U.S. state known for its manufacturing base, rich agricultural land, and iconic events like the Indianapolis 500.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01de4ccc8190aeac4a6c1ffc08d9 |
completed | May 9, 2026, 9:43 a.m. |
Created at: April 10, 2026, 3:17 a.m.