Triple
T3289297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul D |
E69061
|
entity |
| Predicate | hasRelationshipTypeWith |
P10690
|
FINISHED |
| Object | romantic relationship with Sethe |
—
|
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 relationship with Sethe | Statement: [Paul D, hasRelationshipTypeWith, romantic relationship with Sethe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWith Context triple: [Paul D, hasRelationshipTypeWith, romantic relationship with Sethe]
-
A.
hasCentralRelationshipType
Indicates that there exists a primary or most significant type of relationship that characterizes how two entities are related to each other.
-
B.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
C.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
D.
hasKeyRelationship
Indicates a relationship where one entity serves as a key (e.g., identifier, access token, or primary reference) that grants access to, controls, or uniquely identifies another entity.
-
E.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05a3e5c819082552a7a911e3230 |
completed | March 8, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69ada421fadc8190b7c7d3c8afd20061 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.