Triple
T26773711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jessica Pearson |
E670055
|
entity |
| Predicate | settingOfPearson |
P1957
|
FINISHED |
| Object | Chicago |
—
|
NE NERFINISHED |
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: Chicago | Statement: [Jessica Pearson, settingOfPearson, Chicago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfPearson Context triple: [Jessica Pearson, settingOfPearson, Chicago]
-
A.
settingInstitution
Indicates that an entity is associated with or occurs within a particular institution that serves as its setting or context.
-
B.
setting
chosen
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
C.
settingOfTransformation
Indicates the place, context, or environment in which a transformation of an entity or state occurs.
-
D.
settingControlled
Indicates that one entity regulates, adjusts, or determines the configuration or parameters of another entity.
-
E.
indicatedSetting
Indicates that one entity specifies, denotes, or points out a particular setting or configuration associated with another entity.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f65aa07c048190a5df30d53d8f0cf5 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 4:03 a.m.