Triple
T33911176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betty |
E869316
|
entity |
| Predicate | relationshipTypeWithZorg |
P10690
|
FINISHED |
| Object | romantic partner |
—
|
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 partner | Statement: [Betty, relationshipTypeWithZorg, romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithZorg Context triple: [Betty, relationshipTypeWithZorg, romantic partner]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipToDoctor
Indicates the specific personal or professional connection an individual has with a doctor (e.g., self, spouse, parent, guardian, colleague).
-
C.
patientRelationship
Indicates that one entity is the patient or recipient of an action, treatment, or service performed by another entity.
-
D.
referralRelationship
Indicates a relationship in which one entity directs or recommends another entity to a third party for services, information, or further action.
-
E.
relationshipToOrganization
Indicates the nature or type of connection an entity has with a specific organization, such as affiliation, membership, or role.
- 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_69f3499869bc8190b6c33a81686af226 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:48 a.m.