Triple
T28155574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenna Rink |
E714733
|
entity |
| Predicate | romanticStatusAtEnd |
P107707
|
FINISHED |
| Object | married to Matt Flamhaff |
—
|
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: married to Matt Flamhaff | Statement: [Jenna Rink, romanticStatusAtEnd, married to Matt Flamhaff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticStatusAtEnd Context triple: [Jenna Rink, romanticStatusAtEnd, married to Matt Flamhaff]
-
A.
romanticRelationshipStatus
Indicates the nature or state of a romantic relationship between entities, such as whether they are dating, committed, separated, or otherwise romantically involved.
-
B.
romanticOutcome
Indicates that a romantic relationship or interaction between entities results in a particular outcome, such as success, failure, or change in status.
-
C.
relationshipOutcome
Indicates the result or consequence that arises from a particular relationship between two or more entities.
-
D.
hasMaritalStatusAtEnd
chosen
Indicates that an entity possesses a specific marital status at the end of a given period, event, or reference time.
-
E.
engagedTo
Indicates that two entities are formally committed to marry each other.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64dbbaefc8190952b8320bf4397d8 |
completed | May 2, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f64cacd2c08190aed8a1761d0da679 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 27, 2026, 10:02 p.m.