Triple
T20916570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esaú e Jacó |
E515087
|
entity |
| Predicate | protagonistsRelationship |
P27138
|
FINISHED |
| Object | twin brothers |
—
|
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: twin brothers | Statement: [Esaú e Jacó, protagonistsRelationship, twin brothers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistsRelationship Context triple: [Esaú e Jacó, protagonistsRelationship, twin brothers]
-
A.
portraysCharacterRelationship
Indicates that one entity depicts or represents the relationship between characters in another entity.
-
B.
hasProtagonistRelationship
chosen
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
C.
characterActorRelationship
Indicates a relationship where an actor portrays or is associated with a specific character in a work.
-
D.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
-
E.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
- 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec635f4881909a560fb891100d8c |
completed | April 21, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:48 p.m.