Triple
T34248625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Billie Dawn |
E878670
|
entity |
| Predicate | relationshipTypeWith Paul Verrall |
P95781
|
FINISHED |
| Object | student |
—
|
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: student | Statement: [Billie Dawn, relationshipTypeWith Paul Verrall, student]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWith Paul Verrall Context triple: [Billie Dawn, relationshipTypeWith Paul Verrall, student]
-
A.
relationshipTypeWith Lionel Verney
Indicates the specific nature or category of relationship that an entity has with Lionel Verney.
-
B.
relationshipToPaul
chosen
Indicates a specified type of personal or social relationship that an entity has with Paul.
-
C.
relationshipTypeWithScottHipwell
Indicates the specific type or nature of the relationship that an entity has with Scott Hipwell.
-
D.
hasRelationshipTypeWith Vince Tyler
Indicates that an entity is connected to Vince Tyler by a specific, characterized type of relationship.
-
E.
relationshipWithKateMoseley
Indicates that one entity has a specified type of relationship or connection with Kate Moseley.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:56 a.m.