Triple
T15631283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Connelly |
E375816
|
entity |
| Predicate | relationshipStatusWithBradSimon |
P119522
|
FINISHED |
| Object | on-and-off romantic relationship |
—
|
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 romantic relationship | Statement: [Billie Connelly, relationshipStatusWithBradSimon, on-and-off romantic relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithBradSimon Context triple: [Billie Connelly, relationshipStatusWithBradSimon, on-and-off romantic relationship]
-
A.
relationshipStatusWithBrian
Indicates the current nature or state of an entity’s personal relationship with Brian.
-
B.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
C.
relationshipWithBlondie
Indicates that there exists some form of relationship or connection between an entity and Blondie.
-
D.
relationshipStatusWithHoward
Indicates the type or state of the relationship an entity currently has with Howard.
-
E.
relationshipStatusWithKrista
Indicates the current nature or state of an entity’s relationship with Krista.
- 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb536348190b93ed3c178d1ffb8 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:14 a.m.