Triple
T29803274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2019 Toddbrook Reservoir emergency |
E756768
|
entity |
| Predicate | numberOfEvacuatedPeople |
P8973
|
FINISHED |
| Object | approximately 1500 |
—
|
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: approximately 1500 | Statement: [2019 Toddbrook Reservoir emergency, numberOfEvacuatedPeople, approximately 1500]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEvacuatedPeople Context triple: [2019 Toddbrook Reservoir emergency, numberOfEvacuatedPeople, approximately 1500]
-
A.
numberOfEvacuated
chosen
Indicates the total count of individuals who have been evacuated from a location or situation.
-
B.
numberOfChildrenEvacuated
Indicates the total count of children who have been removed from a place or situation for safety or emergency reasons.
-
C.
numberOfTroopsEvacuated
Indicates the quantity of troops that have been removed from a location or situation and transported to safety.
-
D.
numberOfEvacuatedSettlements
Indicates the total count of settlements that have been evacuated.
-
E.
numberOfEvacuatedTonsOfCargo
Indicates the quantity of cargo, measured in tons, that has been evacuated from a location or situation.
- 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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a0017dd31d08190aa5e9f72df83733a |
completed | May 10, 2026, 5:30 a.m. |
| PD | Predicate disambiguation | batch_6a0015a1deb88190b9cdaa60455b0a33 |
completed | May 10, 2026, 5:20 a.m. |
Created at: April 29, 2026, 5:19 p.m.