Triple
T34360078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanjay River |
E881847
|
entity |
| Predicate | hasPotentialIssue |
P45135
|
FINISHED |
| Object | flooding during heavy rains |
—
|
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: flooding during heavy rains | Statement: [Tanjay River, hasPotentialIssue, flooding during heavy rains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPotentialIssue Context triple: [Tanjay River, hasPotentialIssue, flooding during heavy rains]
-
A.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
possibleIssue
chosen
Indicates that there is a potential or suspected problem, defect, or undesired condition associated with the referenced entity or situation, though it is not yet confirmed.
-
C.
containsIssue
Indicates that one entity includes, encompasses, or has within it a particular issue, problem, or defect.
-
D.
hasRecentIssue
Indicates that an entity is associated with an issue or problem that has occurred within a recent or specified time frame.
-
E.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
- 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_69f349be5c9c81908dc726ae1f4c68f2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
Created at: May 1, 2026, 1:58 a.m.