Triple
T17122593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dobu |
E415504
|
entity |
| Predicate | hasReputationInLiterature |
P126061
|
FINISHED |
| Object | hostile interpersonal relations |
—
|
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: hostile interpersonal relations | Statement: [Dobu, hasReputationInLiterature, hostile interpersonal relations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReputationInLiterature Context triple: [Dobu, hasReputationInLiterature, hostile interpersonal relations]
-
A.
hasReputationInFiction
Indicates that an entity is known or regarded in a particular way within fictional works or narratives.
-
B.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
C.
nameInLiterature
Indicates that a particular name is used or appears for an entity within a literary work or context.
-
D.
hasViewOnLiterature
Indicates that an entity holds a particular opinion, perspective, or stance regarding literature.
-
E.
hasLiteraryConnection
Indicates a relationship in which one entity is connected to another through a literary link, such as authorship, reference, influence, adaptation, or shared appearance in written works.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e80ac2cc819084fab829917c950a |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6d20808190a38bb32e2294bc48 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:36 a.m.