Triple
T31710939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Turk |
E809313
|
entity |
| Predicate | hasRelationshipTypeWithJ.D. |
P175131
|
FINISHED |
| Object | roommate at various times |
—
|
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: roommate at various times | Statement: [Christopher Turk, hasRelationshipTypeWithJ.D., roommate at various times]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithJ.D. Context triple: [Christopher Turk, hasRelationshipTypeWithJ.D., roommate at various times]
-
A.
hasRelationshipTypeWith Anastasia Steele
Indicates that an entity has a specific type of relationship or relational role with Anastasia Steele.
-
B.
hasRelationshipTypeWithRocky
Indicates that an entity has a specific type of relationship or connection with the entity named Rocky.
-
C.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
D.
hasRelationshipTypeWith Owen Hunt
Indicates that there exists a specific type of interpersonal or relational connection between an entity and Owen Hunt.
-
E.
haveRelationshipWith
chosen
Indicates that one entity is in some form of defined relationship or association with another entity.
- 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_69f348df4e048190a4a5a9932ada78d6 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0191d96dc88190ac0823e534f9d704 |
completed | May 11, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_6a01908110448190a46442ffe4d15f5f |
completed | May 11, 2026, 8:17 a.m. |
Created at: April 30, 2026, 11:15 p.m.