Triple
T6488450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acrisius |
E146572
|
entity |
| Predicate | reasonForImprisoningDanae |
P71012
|
FINISHED |
| Object | to prevent her from bearing a 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: to prevent her from bearing a child | Statement: [Acrisius, reasonForImprisoningDanae, to prevent her from bearing a child]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForImprisoningDanae Context triple: [Acrisius, reasonForImprisoningDanae, to prevent her from bearing a child]
-
A.
punishmentOfPrometheus
Indicates the punitive action or suffering that is inflicted upon Prometheus as a consequence of his deeds.
-
B.
attemptedAbductionWithPirithous
Indicates an event where an entity participated with Pirithous in an attempt to abduct someone.
-
C.
reasonForConviction
Indicates the specific offense or legal basis for which an individual was found guilty or convicted.
-
D.
AphroditeBribe
Indicates that one entity (Aphrodite) offers or gives a persuasive incentive or reward to another entity in order to influence their decision or allegiance.
-
E.
HeraBribe
Indicates that Hera offers something of value as a bribe to influence or persuade another entity to act in her favor.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a97fff88190b6f993c14df62649 |
completed | March 22, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69c06740bebc81909d9d6956baa2bcb9 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067f1ef148190bc0355abe83f7e16 |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:52 p.m.