Triple
T31175975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hercules |
E794747
|
entity |
| Predicate | performsLaborsAsPenanceFor |
P194314
|
FINISHED |
| Object | murder of his children |
—
|
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: murder of his children | Statement: [Hercules, performsLaborsAsPenanceFor, murder of his children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performsLaborsAsPenanceFor Context triple: [Hercules, performsLaborsAsPenanceFor, murder of his children]
-
A.
performedPenanceTo
chosen
Indicates that one entity carried out acts of penance directed toward or in relation to another entity.
-
B.
performedPenanceAt
Indicates that an entity carried out an act of penance at a specific place or location.
-
C.
goalOfPenance
Indicates that an action or practice is performed with the specific purpose of making amends, seeking forgiveness, or achieving spiritual or moral purification.
-
D.
penance
Indicates an act of self-imposed suffering, discipline, or reparation performed to atone for a wrongdoing or moral failing.
-
E.
repentsFor
Indicates that one entity feels remorse or regret for an action, wrongdoing, or harm related to another entity.
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd8e5f7c4c8190ab8e2f2a7bb1bd79 |
completed | May 8, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fd8d8a16f08190b9e880901bfa44fe |
completed | May 8, 2026, 7:15 a.m. |
Created at: April 29, 2026, 9:08 p.m.