Triple
T15905130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Jeffrey Squires |
E385691
|
entity |
| Predicate | relationshipToStephanie |
P114501
|
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: [Dr. Jeffrey Squires, relationshipToStephanie, lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToStephanie Context triple: [Dr. Jeffrey Squires, relationshipToStephanie, lover]
-
A.
relationshipTypeWithStephanie Ramzinski
chosen
Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
-
B.
relationshipWithStephano
Indicates a relationship or connection that an entity has with Stephano, without specifying the type or nature of that relationship.
-
C.
stepSister
Indicates that one person is the female child of a parent who is married to, but not the biological or adoptive parent of, another person, making her that person’s stepsister.
-
D.
relationshipToSophie
Indicates the specific type of personal or social connection that an entity has to Sophie.
-
E.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142ca3b208190946c3aa4c1e6087c |
completed | April 16, 2026, 8:12 p.m. |
Created at: April 10, 2026, 4:52 a.m.