Triple
T19812526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mandakini River valley |
E475980
|
entity |
| Predicate | disasterHistory |
P137414
|
FINISHED |
| Object | 2013 North India floods |
—
|
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: 2013 North India floods | Statement: [Mandakini River valley, disasterHistory, 2013 North India floods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disasterHistory Context triple: [Mandakini River valley, disasterHistory, 2013 North India floods]
-
A.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
B.
notableDisasterType
Indicates the specific kind or category of disaster for which something (such as a place, event, or entity) is notable or best known.
-
C.
disasterName
Indicates the specific name or title assigned to a particular disaster event.
-
D.
impactOfDisasters
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
-
E.
disasterLocation
Indicates the place where a disaster occurs or has its primary impact.
- 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6542d7c048190818359cbf430f50e |
completed | April 20, 2026, 4:28 p.m. |
| PD | Predicate disambiguation | batch_69e5305858108190bbbfdb9ba3ab9f80 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bcf41c8190b685b5adf46a60fc |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:50 p.m.