Triple
T34083765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marries former escort Willa Ferreyra |
E874119
|
entity |
| Predicate | followsRelationshipType |
P10690
|
FINISHED |
| Object | longTermCohabitation |
—
|
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: longTermCohabitation | Statement: [Marries former escort Willa Ferreyra, followsRelationshipType, longTermCohabitation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followsRelationshipType Context triple: [Marries former escort Willa Ferreyra, followsRelationshipType, longTermCohabitation]
-
A.
followsRelationshipOf
Indicates that one entity follows, succeeds, or comes after another in a sequence, order, or relational chain.
-
B.
followsBy
Indicates that one event, state, or entity occurs or comes immediately after another in a sequence or order.
-
C.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
followsBetween
Indicates that one entity comes after or succeeds another entity within a specified context or sequence.
-
E.
followsTo
Indicates that one entity moves or proceeds behind another entity toward a specific destination or target.
- 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_69f349a61d448190b74642f325d3eb7a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fea5e828cc8190a9b755a645dc56d2 |
completed | May 9, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69fea36443f08190b2aced9b4a0525fd |
completed | May 9, 2026, 3 a.m. |
Created at: May 1, 2026, 1:52 a.m.