Triple
T25942768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suzanne Verdal |
E653750
|
entity |
| Predicate | knownForRelationshipTo |
P149729
|
FINISHED |
| Object | Leonard Cohen |
—
|
NE NERFINISHED |
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: Leonard Cohen | Statement: [Suzanne Verdal, knownForRelationshipTo, Leonard Cohen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForRelationshipTo Context triple: [Suzanne Verdal, knownForRelationshipTo, Leonard Cohen]
-
A.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
B.
relationshipTarget
chosen
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
-
C.
nowKnownFor
Indicates that an entity is currently recognized or notable for a particular role, attribute, achievement, or association.
-
D.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
-
E.
showsRelationshipWith
Indicates that one entity visually or explicitly presents or demonstrates its connection 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_69e7ab3fd2f881908837305e4ba98011 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 22, 2026, 8:41 a.m.