Triple
T16467913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wellington |
E399981
|
entity |
| Predicate | hasAdjacentStation |
P231
|
FINISHED |
| Object | Diversey |
E366591
|
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: Diversey | Statement: [Wellington, hasAdjacentStation, Diversey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Diversey Context triple: [Wellington, hasAdjacentStation, Diversey]
-
A.
Diversey
chosen
Diversey is a Chicago Transit Authority 'L' station on the Brown Line located in the Lincoln Park/Lakeview area of Chicago.
-
B.
Diversey Harbor
Diversey Harbor is a popular Chicago marina on Lake Michigan known for its boating facilities and proximity to Lincoln Park.
-
C.
Nalco Company
Nalco Company is a global water treatment and process improvement firm known for producing industrial chemicals, including the oil spill dispersant Corexit 9500A.
-
D.
Kohler Company
Kohler Company is a prominent American manufacturer best known for its kitchen and bath fixtures, engines, and power systems, as well as its hospitality and real estate ventures.
-
E.
Pentair
Pentair is a global water treatment and fluid management company known for providing technologies and solutions for residential, commercial, industrial, and infrastructure applications.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dcd707081908fb7ca91a8c09e0a |
completed | April 18, 2026, 7:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f5914dc81908c3b8cf999ee76a1 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:11 a.m.