Triple
T5556310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Croatia and Serbia |
E145650
|
entity |
| Predicate | haveOpenIssuesRegarding |
P29037
|
FINISHED |
| Object | warLegacy |
—
|
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: warLegacy | Statement: [Croatia and Serbia, haveOpenIssuesRegarding, warLegacy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveOpenIssuesRegarding Context triple: [Croatia and Serbia, haveOpenIssuesRegarding, warLegacy]
-
A.
numberOfIssues
Indicates the quantity of issues associated with a given entity or context.
-
B.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
C.
hasTargetIssue
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
-
D.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
E.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
- 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_69c008fcaf788190bafa02a1917ee73b |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01ffc5e7c81908e1c454d3bfd357b |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b10bbf8819098655839c03b7832 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:36 p.m.