Triple
T38185022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael II Asen of Bulgaria |
E1005290
|
entity |
| Predicate | internalProblems |
P33633
|
FINISHED |
| Object | boyar factionalism |
—
|
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: boyar factionalism | Statement: [Michael II Asen of Bulgaria, internalProblems, boyar factionalism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: internalProblems Context triple: [Michael II Asen of Bulgaria, internalProblems, boyar factionalism]
-
A.
hasInternalIssue
chosen
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
B.
conditionIssues
Indicates that one entity has problems, defects, or concerns related to the state or condition of another entity.
-
C.
issues
Indicates that an entity formally produces, releases, or distributes something, such as a document, order, or resource, making it officially available.
-
D.
problems
Indicates that one entity has issues, difficulties, or complications associated with or caused by another entity.
-
E.
knownIssue
Indicates that the subject has an issue or problem that is already identified, recognized, or documented.
- 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: May 3, 2026, 4:29 p.m.