Triple
T35289740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steven Stayner |
E1019187
|
entity |
| Predicate | residenceDuringCaptivity |
P151405
|
FINISHED |
| Object | Santa Rosa, California, United States |
—
|
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: Santa Rosa, California, United States | Statement: [Steven Stayner, residenceDuringCaptivity, Santa Rosa, California, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: residenceDuringCaptivity Context triple: [Steven Stayner, residenceDuringCaptivity, Santa Rosa, California, United States]
-
A.
periodOfCaptivity
Indicates a time span during which an entity is held in captivity or confinement.
-
B.
residenceDuringImprisonment
chosen
Indicates that an entity’s place of residence is specified for the period during which that entity is imprisoned.
-
C.
wasImprisonedIn
Indicates that an entity was held in confinement or incarcerated at a particular place or facility.
-
D.
residenceBeforeImprisonment
Indicates the place where an individual lived prior to being imprisoned.
-
E.
heldTitleWhileInCaptivity
Indicates that an entity continued to hold a specific title or position during a period when they were in captivity.
- 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_69f76de6d39c8190bb11342e4b91ff2b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.