Triple
T24132067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anika Calhoun |
E597980
|
entity |
| Predicate | relationshipTypeWithHakeemLyon |
P154960
|
FINISHED |
| Object | romantic and co-parenting |
—
|
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: romantic and co-parenting | Statement: [Anika Calhoun, relationshipTypeWithHakeemLyon, romantic and co-parenting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithHakeemLyon Context triple: [Anika Calhoun, relationshipTypeWithHakeemLyon, romantic and co-parenting]
-
A.
hasRelationshipTypeWithJamalLyon
Indicates that an entity has a specific type of interpersonal relationship with Jamal Lyon.
-
B.
relationshipTypeWithAndreLyon
Indicates the specific nature or category of relationship that an entity has with Andre Lyon.
-
C.
relationshipToAkeem
Indicates the specific type of personal or social relationship that an entity has with Akeem.
-
D.
relationshipTypeWith Hank Evans
Indicates the specific nature or category of the relationship that an entity has with Hank Evans.
-
E.
relationshipToLouisHinds
Indicates the specific familial, social, or professional relationship that an entity has to Louis Hinds.
- F. None of above. chosen
Provenance (4 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_69e288c808b881909fed7d18f04bcbbe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1df78b6f08190809fc154110fa201 |
completed | April 29, 2026, 10:37 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f17c28b684819084eea522126463f8 |
completed | April 29, 2026, 3:34 a.m. |
Created at: April 17, 2026, 11:25 p.m.