Triple
T3578453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koshi River |
E75742
|
entity |
| Predicate | 2008FloodImpact |
P39938
|
FINISHED |
| Object | displacement of over a million people in Bihar |
—
|
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: displacement of over a million people in Bihar | Statement: [Koshi River, 2008FloodImpact, displacement of over a million people in Bihar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 2008FloodImpact Context triple: [Koshi River, 2008FloodImpact, displacement of over a million people in Bihar]
-
A.
floodEvent
chosen
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
B.
floodCause
Indicates that one entity is the cause or source of a flood affecting another entity or area.
-
C.
notableFloodEvents
Indicates that there are significant or historically important flood occurrences associated with the given entity.
-
D.
floodRecord
Indicates that an entity serves as a documented record or report of a flood event affecting another entity or area.
-
E.
floodSeasonCause
Indicates the cause or contributing factor responsible for a particular flood season occurring.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0defe14819095a337a840e33300 |
completed | March 8, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.