Triple
T33772986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamie |
E865434
|
entity |
| Predicate | relationshipStatusWithNina |
P203028
|
FINISHED |
| Object | former romantic partner |
—
|
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 romantic partner | Statement: [Jamie, relationshipStatusWithNina, former romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithNina Context triple: [Jamie, relationshipStatusWithNina, former romantic partner]
-
A.
relationshipToNina
chosen
Indicates that one entity has a specified personal or social relationship to Nina.
-
B.
relationshipStatusWithAnna
Indicates the type or state of the relationship that an entity currently has with Anna.
-
C.
relationshipToNicole
Indicates the specific type of relationship or connection that an entity has with Nicole.
-
D.
relationshipToTina
Indicates the specific type of personal or social relationship that an entity has with Tina.
-
E.
relationshipStatusWithNP
Indicates the type or state of a relationship that one entity has with a specified noun phrase (NP).
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:45 a.m.