Triple
T33703977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorcas |
E863533
|
entity |
| Predicate | causeEffect |
P694
|
FINISHED |
| Object | her restoration to life led many to believe in the Lord |
—
|
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: her restoration to life led many to believe in the Lord | Statement: [Dorcas, causeEffect, her restoration to life led many to believe in the Lord]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causeEffect Context triple: [Dorcas, causeEffect, her restoration to life led many to believe in the Lord]
-
A.
causeOf
chosen
Indicates that one entity brings about, produces, or is responsible for the occurrence or existence of another entity or event.
-
B.
causeOfAction
Indicates that one entity is the reason or basis for initiating a legal action or lawsuit against another entity.
-
C.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
D.
causeDescribedAs
Indicates that one entity is described or characterized as the cause of another entity or event.
-
E.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 1, 2026, 1:43 a.m.