Triple
T38335305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Carolyn |
E1037938
|
entity |
| Predicate | relationshipTypeWithJudahMannowdog |
P204607
|
FINISHED |
| Object | business 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: business partner | Statement: [Princess Carolyn, relationshipTypeWithJudahMannowdog, business partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithJudahMannowdog Context triple: [Princess Carolyn, relationshipTypeWithJudahMannowdog, business partner]
-
A.
relationshipToManni
Indicates a relational connection that an entity has specifically with Manni, such as their role, association, or familial/ social tie to Manni.
-
B.
relationshipTypeWithJudith
Indicates the specific type or nature of the relationship that an entity has with Judith.
-
C.
opusRelationship
Indicates a relationship between creative works (opuses), such as versions, adaptations, or parts within a larger compositional whole.
-
D.
relationshipTypeWithMarvin
Indicates the specific nature or category of the relationship an entity has with Marvin.
-
E.
relationshipToFelix
Indicates the specific type of relationship or connection that an entity has with Felix.
- 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_69f76e20d65c81909619ac0dd85c56f0 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.