Triple
T37373922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musette |
E927919
|
entity |
| Predicate | relationshipTypeWithMarcello |
P134611
|
FINISHED |
| Object | on-and-off 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: on-and-off lover | Statement: [Musette, relationshipTypeWithMarcello, on-and-off lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithMarcello Context triple: [Musette, relationshipTypeWithMarcello, on-and-off lover]
-
A.
relationshipWithMarcello
chosen
Indicates that there exists some form of relationship or connection between an entity and Marcello.
-
B.
relationshipTypeWithMarvin
Indicates the specific nature or category of the relationship an entity has with Marvin.
-
C.
relationshipToMaria
Indicates the specific type of relationship or connection that an entity has to Maria.
-
D.
relationshipToMariane
Indicates the specific type of relationship or connection that an entity has to Mariane.
-
E.
relationshipToMarcy
Indicates that one entity has a specified personal or social relationship to Marcy.
- 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_69f76eb820248190a5c395ca50ad002a |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.