Triple
T8514578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannibalianus |
E201539
|
entity |
| Predicate | hasNoIssue |
P82927
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hannibalianus, hasNoIssue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoIssue Context triple: [Hannibalianus, hasNoIssue, true]
-
A.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
C.
hasKeyIssue
Indicates that an entity is associated with a primary or central problem, concern, or topic of importance.
-
D.
doesNotIssue
Indicates that one entity refrains from or fails to produce, grant, or distribute something (such as a document, order, or resource) to another entity.
-
E.
hasTargetIssue
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
- 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_69ca8320e5748190ac2c585a0bba8193 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe60e12848190a4a3dfa457aef275 |
completed | March 31, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69cbd10cfd208190a519049fad32c508 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:15 p.m.