Triple
T3481682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngunnawal people |
E73503
|
entity |
| Predicate | hasOngoingIssue |
P20553
|
FINISHED |
| Object | land rights claims |
—
|
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: land rights claims | Statement: [Ngunnawal people, hasOngoingIssue, land rights claims]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOngoingIssue Context triple: [Ngunnawal people, hasOngoingIssue, land rights claims]
-
A.
hasInternalIssue
Indicates that an entity is experiencing a problem, fault, or malfunction originating within itself or its internal components or processes.
-
B.
hasOngoingConflict
chosen
Indicates that there is a current, unresolved state of opposition, dispute, or hostilities between the related entities.
-
C.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
D.
hasPracticeIssue
Indicates that an entity is associated with a specific problem, concern, or challenge arising in practical or real-world practice.
-
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.
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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb75850c8190ad02cf2bde8be8a7 |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.