Triple
T9202830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gurnee, Illinois |
E220888
|
entity |
| Predicate | Walter S. GurneeOccupation |
P12884
|
FINISHED |
| Object | former mayor of Chicago |
—
|
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: former mayor of Chicago | Statement: [Gurnee, Illinois, Walter S. GurneeOccupation, former mayor of Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Walter S. GurneeOccupation Context triple: [Gurnee, Illinois, Walter S. GurneeOccupation, former mayor of Chicago]
-
A.
namedPersonOccupation
chosen
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
MajorWalterReedWas
Indicates that the subject is being identified as Major Walter Reed, specifying that they held or are associated with that particular name and rank.
-
C.
honoreeKnownFor
Indicates that an honoree is recognized or celebrated specifically for a particular work, achievement, contribution, or notable attribute.
-
D.
sonOccupation
Indicates that a specified occupation is the job or professional role held by a person's son.
-
E.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
- 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_69ca83e8e9248190862cf3e41693b310 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd943cfb0819082231d80f0dc073b |
completed | April 1, 2026, 8:37 a.m. |
| PD | Predicate disambiguation | batch_69cc660af2408190ae06eb8326e1c64e |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:26 p.m.