Triple
T10378333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lily |
E244564
|
entity |
| Predicate | relationshipTypeWithNinaSayers |
P93674
|
FINISHED |
| Object | rivalry |
—
|
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: rivalry | Statement: [Lily, relationshipTypeWithNinaSayers, rivalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithNinaSayers Context triple: [Lily, relationshipTypeWithNinaSayers, rivalry]
-
A.
relationshipTypeWithJanieCrawford
Indicates the specific nature or category of relationship that an entity has with Janie Crawford.
-
B.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
C.
relationshipToMargoChanning
Indicates the nature or type of relationship an entity has with Margo Channing.
-
D.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
E.
relationshipToDianaGoodman
Indicates a specified type of relationship or connection that an entity has to Diana Goodman.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e98fead88190ace49f34b8a27c25 |
completed | April 7, 2026, 11:25 a.m. |
| PD | Predicate disambiguation | batch_69d4dface5508190a7b42f01ad0a19a2 |
completed | April 7, 2026, 10:42 a.m. |
| PDg | Predicate description generation | batch_69d4e944fac4819093b0312aa0efd729 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:03 p.m.