Triple
T34392293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nurse Betty Sizemore |
E882734
|
entity |
| Predicate | causeOfDelusion |
P192173
|
FINISHED |
| Object | witnessing a brutal killing |
—
|
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: witnessing a brutal killing | Statement: [Nurse Betty Sizemore, causeOfDelusion, witnessing a brutal killing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeOfDelusion Context triple: [Nurse Betty Sizemore, causeOfDelusion, witnessing a brutal killing]
-
A.
causeOf
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
causeInStory
Indicates that one event, action, or state functions as the cause of another within the narrative structure of a story.
-
C.
causeOfCompulsion
Indicates that one entity is the reason or driving factor behind another entity’s sense of compulsion or irresistible urge to act.
-
D.
causeDescribedAs
Indicates that one entity is described or characterized as the cause of another entity or event.
-
E.
causeStatus
Indicates that one entity brings about, initiates, or is responsible for a particular state or condition in another entity.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
| PDg | Predicate description generation | batch_69fcf82405c88190a19cecf8e9cc272d |
completed | May 7, 2026, 8:37 p.m. |
Created at: May 1, 2026, 1:59 a.m.