Triple
T20720080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cléante |
E509286
|
entity |
| Predicate | hasRelationshipTypeWithAngélique |
P141251
|
FINISHED |
| Object | lover |
—
|
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: lover | Statement: [Cléante, hasRelationshipTypeWithAngélique, lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithAngélique Context triple: [Cléante, hasRelationshipTypeWithAngélique, lover]
-
A.
hasRelationshipTypeWith Valère
Indicates that an entity stands in a specific, characterized type of relationship with Valère.
-
B.
relationshipTypeWithAlceste
Indicates the specific nature or category of relationship that an entity has with Alceste.
-
C.
relationshipToOdette
Indicates the specific familial, social, or interpersonal connection that an entity has with Odette.
-
D.
relationshipTypeWithJulie d’Étange
Indicates the specific nature or category of the relationship that an entity has with Julie d’Étange.
-
E.
hasRelationshipTypeWith Alexandra Bergson
Indicates that there exists a specific type or category of relationship between an entity and Alexandra Bergson.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1d4de6c81908f8c98c2f1e70cc4 |
completed | April 21, 2026, 12:16 a.m. |
| PD | Predicate disambiguation | batch_69e5c04b31248190b9b9d91b5cb854e3 |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3caef50819093c8159fe8d6435b |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:26 p.m.