Triple
T20663030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellie Cavanaugh |
E507805
|
entity |
| Predicate | ageAtSisterMurder |
P140968
|
FINISHED |
| Object | child |
—
|
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: child | Statement: [Ellie Cavanaugh, ageAtSisterMurder, child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtSisterMurder Context triple: [Ellie Cavanaugh, ageAtSisterMurder, child]
-
A.
Mary Bell
Indicates a relationship or action involving an entity named Mary Bell, though the specific nature of the relationship or action is not defined by the predicate alone.
-
B.
ageAtTimeOfAccusation
Indicates the age a person was at the specific time when an accusation was made against them.
-
C.
ageAtKidnapping
Indicates the age a person was at the time they were kidnapped.
-
D.
ageAtTimeOfConvictionInStory
Indicates the age a person was at the specific time they were convicted within the context or timeline of the story.
-
E.
numberOfChildrenMurdered
Indicates the count of children who have been killed in an act of murder.
- F. None of above. chosen
Provenance (4 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_69e0b4c059bc81908ea762cd73ea4424 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6b2f4872481908858eb88ce89dd47 |
completed | April 20, 2026, 11:12 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 11:44 a.m.