Triple
T35173893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanderson, Texas |
E1015634
|
entity |
| Predicate | majorEventEffect |
P53074
|
FINISHED |
| Object | severe flash flooding and damage |
—
|
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: severe flash flooding and damage | Statement: [Sanderson, Texas, majorEventEffect, severe flash flooding and damage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorEventEffect Context triple: [Sanderson, Texas, majorEventEffect, severe flash flooding and damage]
-
A.
impactOfNotableEvent
Indicates the causal influence or consequences that a specific notable event has on an entity, situation, or outcome.
-
B.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
significantEventConsequence
Indicates that one event leads to an important or impactful consequence for another event, state, or entity.
-
D.
majorEventContext
Indicates that one event occurs in the context of, or is significantly shaped by, a larger major event or overarching situation.
-
E.
significantEvent
Indicates that an event involving the entities is of notable importance or impact within a given context.
- 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff795d25d08190b7584c72be39d309 |
completed | May 9, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69ff78a90fbc8190a62c57456dc1d4ad |
completed | May 9, 2026, 6:10 p.m. |
Created at: May 3, 2026, 4:02 p.m.