Triple
T5700834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Bowne |
E125655
|
entity |
| Predicate | arrestReason |
P15395
|
FINISHED |
| Object | holding Quaker meetings in his home |
—
|
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: holding Quaker meetings in his home | Statement: [John Bowne, arrestReason, holding Quaker meetings in his home]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrestReason Context triple: [John Bowne, arrestReason, holding Quaker meetings in his home]
-
A.
arrestedFor
chosen
Indicates that an authority has taken someone into custody because they are suspected or accused of committing a specified offense or wrongdoing.
-
B.
arrestedAt
Indicates that an entity was apprehended or taken into custody at a specific location or during a specific event or time.
-
C.
arrests
Indicates that one entity, typically an authority figure, seizes and detains another entity under legal or official power.
-
D.
attemptedArrestBy
Indicates that one entity tried, but may not have succeeded, to place another entity under arrest.
-
E.
arrestContext
Indicates that an arrest event occurs within a particular situational, legal, or environmental context that frames how and why the arrest takes place.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024540afc8190aee3760f71ea39c2 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.