Triple
T31100846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Janey Slater |
E792667
|
entity |
| Predicate | relationshipStatusWithJonOsterman |
P207351
|
FINISHED |
| Object | former girlfriend |
—
|
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: former girlfriend | Statement: [Janey Slater, relationshipStatusWithJonOsterman, former girlfriend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithJonOsterman Context triple: [Janey Slater, relationshipStatusWithJonOsterman, former girlfriend]
-
A.
relationshipToJoni
Indicates the specific familial, social, or professional connection that one entity has to the person or entity named Joni.
-
B.
relationshipStatusWithJoeyPotter
Indicates the nature or state of an entity’s personal or romantic relationship with Joey Potter.
-
C.
relationshipToSheldonCooper
Indicates the specific interpersonal or familial connection that an entity has to Sheldon Cooper.
-
D.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
E.
relationshipTypeWithJonArbuckle
Indicates the specific nature or category of relationship that an entity has with Jon Arbuckle.
- 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_69f224cf157c81909e2d2bd88c9282c3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:03 p.m.