Triple
T21957059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cléonte |
E542217
|
entity |
| Predicate | relationshipToMonsieurJourdain |
P146694
|
FINISHED |
| Object | suitor to his daughter |
—
|
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: suitor to his daughter | Statement: [Cléonte, relationshipToMonsieurJourdain, suitor to his daughter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMonsieurJourdain Context triple: [Cléonte, relationshipToMonsieurJourdain, suitor to his daughter]
-
A.
relationshipTypeWithManonLescaut
Indicates the specific nature or category of relationship that an entity has with Manon Lescaut.
-
B.
relationshipToGoriot
Indicates the type or nature of a person's relationship to Goriot.
-
C.
relationshipToBaudelaires
Indicates the type of personal or familial connection an entity has to the Baudelaires.
-
D.
relationshipToAngélique
Indicates the specific type of personal, social, or familial relationship that one entity has to Angélique.
-
E.
relationshipTypeWithEugénieGrandet
Indicates the specific nature or category of relationship an entity has with Eugénie Grandet.
- 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_69e0c47ef0e48190a50e1bcc43f4b3fd |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1244108948190a08e6966e55c4acd |
completed | April 28, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69e6f601f2188190893bcdde0cf58ad6 |
completed | April 21, 2026, 3:58 a.m. |
| PDg | Predicate description generation | batch_69e6fb9b75308190addc3dba7b5d5ddd |
completed | April 21, 2026, 4:22 a.m. |
Created at: April 16, 2026, 7:59 p.m.