Triple
T29007185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butler’s Woman Order |
E736467
|
entity |
| Predicate | consequenceThreatened |
P161957
|
FINISHED |
| Object | women could be arrested as prostitutes |
—
|
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: women could be arrested as prostitutes | Statement: [Butler’s Woman Order, consequenceThreatened, women could be arrested as prostitutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceThreatened Context triple: [Butler’s Woman Order, consequenceThreatened, women could be arrested as prostitutes]
-
A.
threatenedOutcome
chosen
Indicates that one entity has communicated an intention or warning that a particular outcome or consequence may occur.
-
B.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
C.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
D.
consequenceOfDestruction
Indicates that one event, state, or condition occurs as a direct result of a prior act of destruction.
-
E.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 28, 2026, 9:39 a.m.