Triple
T31598059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perry Wright |
E806271
|
entity |
| Predicate | hasRelationshipTypeWithCeleste |
P203431
|
FINISHED |
| Object | abusive marriage |
—
|
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: abusive marriage | Statement: [Perry Wright, hasRelationshipTypeWithCeleste, abusive marriage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationshipTypeWithCeleste Context triple: [Perry Wright, hasRelationshipTypeWithCeleste, abusive marriage]
-
A.
hasRelationshipTypeWith Anastasia Steele
Indicates that an entity has a specific type of relationship or relational role with Anastasia Steele.
-
B.
relationshipToCelestina
Indicates the specific type of personal, social, or familial relationship that one entity has to Celestina.
-
C.
hasRelationshipTypeWithMerlin
Indicates that an entity has a specific type of relationship or connection with Merlin.
-
D.
hasRelationshipTypeWith Valère
Indicates that an entity stands in a specific, characterized type of relationship with Valère.
-
E.
hasRelationshipTypeWithAngélique
Indicates that one entity has a specific type of relationship or relational status with Angélique.
- 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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a017d27e184819094638c3cf6876de4 |
completed | May 11, 2026, 6:54 a.m. |
| PD | Predicate disambiguation | batch_6a017c785a44819083111384b55769e9 |
completed | May 11, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_6a017d270e9881909e70280ff4e45e9a |
completed | May 11, 2026, 6:54 a.m. |
Created at: April 30, 2026, 10:31 p.m.