Triple
T16868510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byron Hadley |
E410105
|
entity |
| Predicate | treatsPrisoners |
P115931
|
FINISHED |
| Object | abusively |
—
|
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: abusively | Statement: [Byron Hadley, treatsPrisoners, abusively]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsPrisoners Context triple: [Byron Hadley, treatsPrisoners, abusively]
-
A.
effectOnPrisoners
Indicates the impact or consequences that something has on prisoners.
-
B.
treatmentOfInternees
chosen
Indicates how individuals who are interned or detained are handled, managed, or treated by the responsible authorities or entities.
-
C.
prisonersOfWar
Indicates a relationship where certain individuals are held in custody by an enemy during an armed conflict as prisoners of war.
-
D.
hasPrisoners
Indicates that an entity holds or contains one or more individuals who are imprisoned or detained.
-
E.
inmates
Indicates that one entity is confined or held as a prisoner within an institution or facility 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b50a82348190b3e33fd558aa3c7f |
completed | April 18, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.