Triple
T25364617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Dattolo |
E636064
|
entity |
| Predicate | relationshipStatusWithMarnie |
P183470
|
FINISHED |
| Object | on-and-off boyfriend |
—
|
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 boyfriend | Statement: [Charlie Dattolo, relationshipStatusWithMarnie, on-and-off boyfriend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithMarnie Context triple: [Charlie Dattolo, relationshipStatusWithMarnie, on-and-off boyfriend]
-
A.
relationshipToMariane
Indicates the specific type of relationship or connection that an entity has to Mariane.
-
B.
relationshipToMarcy
Indicates that one entity has a specified personal or social relationship to Marcy.
-
C.
relationshipToMary
Indicates that one entity stands in a specified personal or social relationship to Mary.
-
D.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
E.
relationshipStatusWithCarrie
Indicates the current nature or state of an entity’s relationship with Carrie.
- 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_69e75a9b7cf481909f2dcdfb37d95ca7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f7a01efcc08190bba489a9099b8684 |
completed | May 3, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
| PDg | Predicate description generation | batch_69f79f477c4c8190a35cb6d87b1dcbd1 |
completed | May 3, 2026, 7:17 p.m. |
Created at: April 21, 2026, 1:36 p.m.