Triple
T13681532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | healing of the paralytic at Bethesda |
E328014
|
entity |
| Predicate | causesReactionFrom |
P97670
|
FINISHED |
| Object | Jewish authorities |
—
|
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: Jewish authorities | Statement: [healing of the paralytic at Bethesda, causesReactionFrom, Jewish authorities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: causesReactionFrom Context triple: [healing of the paralytic at Bethesda, causesReactionFrom, Jewish authorities]
-
A.
causedReaction
chosen
Indicates that one entity’s action or state brought about a specific reaction or response in another entity.
-
B.
relatedReaction
Indicates that one reaction is connected or associated with another reaction in some relevant way.
-
C.
featuresReaction
Indicates that one entity exhibits, displays, or includes a particular reaction associated with another entity or context.
-
D.
receivedReaction
Indicates that an entity has been the target of a reaction or response from another entity.
-
E.
netReaction
Indicates the overall chemical transformation resulting from combining all individual reaction steps, showing only the net change between reactants and products.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc66e75188190a9e82fdc5eb26513 |
completed | April 12, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.