Triple
T21761880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myrrha |
E537182
|
entity |
| Predicate | relationshipWithCinyras |
P145828
|
FINISHED |
| Object | deceived him into sleeping with her |
—
|
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: deceived him into sleeping with her | Statement: [Myrrha, relationshipWithCinyras, deceived him into sleeping with her]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithCinyras Context triple: [Myrrha, relationshipWithCinyras, deceived him into sleeping with her]
-
A.
relationshipToDeianira
Indicates a specified type of relationship that one entity has to Deianira, such as familial, romantic, or social connection.
-
B.
relationshipToHeracles
Indicates the specific familial or social relationship that an entity has to Heracles.
-
C.
relationshipToCarmen
Indicates the specific type of personal or social relationship an entity has with Carmen.
-
D.
relationshipToNerissa
Indicates the specific type of personal, social, or familial relationship that one entity has with Nerissa.
-
E.
relationshipWithAphrodite
Indicates a romantic, familial, or otherwise significant interpersonal connection that an entity has with Aphrodite.
- 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_69e0c46f5d1c8190bf830409e98464e5 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d9369f88190b4be11b82fe75a17 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6be6299988190a34c98fa76d94700 |
completed | April 21, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69e6d054737081908aa7112975b77475 |
completed | April 21, 2026, 1:18 a.m. |
Created at: April 16, 2026, 6:51 p.m.