Triple
T19704630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myrtha |
E473179
|
entity |
| Predicate | relationshipToAlbrecht |
P137012
|
FINISHED |
| Object | would-be executioner |
—
|
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: would-be executioner | Statement: [Myrtha, relationshipToAlbrecht, would-be executioner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToAlbrecht Context triple: [Myrtha, relationshipToAlbrecht, would-be executioner]
-
A.
relationshipToGustav von Aschenbach
Indicates the specific type of personal, social, or emotional connection an entity has to Gustav von Aschenbach.
-
B.
relationshipToCharlesV
Indicates the specific familial or social relationship that one entity has to Charles V.
-
C.
relationshipWithAlbertDeMorcerf
Indicates that there exists some form of relationship, connection, or association between an entity and Albert de Morcerf.
-
D.
relativeTypeToJohannSebastianBach
Indicates a familial relationship that a person has to Johann Sebastian Bach (e.g., parent, child, sibling, spouse, or other relative).
-
E.
relationshipToJoachimZiemßen
Indicates the nature of a person's relationship or connection to Joachim Ziemßen.
- 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e642b998608190a82f23bbf77f7bd2 |
completed | April 20, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69e530438c60819082364c7be3eef6f0 |
completed | April 19, 2026, 7:42 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.