Triple
T35922903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Francis Dam disaster |
E1038932
|
entity |
| Predicate | timeToEmptyReservoir |
P184231
|
FINISHED |
| Object | about 70 minutes |
—
|
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: about 70 minutes | Statement: [St. Francis Dam disaster, timeToEmptyReservoir, about 70 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToEmptyReservoir Context triple: [St. Francis Dam disaster, timeToEmptyReservoir, about 70 minutes]
-
A.
reservoirLength
Indicates the measured longitudinal extent of a reservoir from one end to the other.
-
B.
reservoirAge
Indicates the length of time that a reservoir has existed or been in use.
-
C.
waterVolume
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
D.
reservoir
Indicates that one entity serves as a storage or containment source (often for a resource) that can supply or affect another entity.
-
E.
reservoirVolumeReleased
Indicates the amount of water discharged from a reservoir over a specified period or event.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69f7ac2210e481909279dade5328825c |
completed | May 3, 2026, 8:12 p.m. |
Created at: May 3, 2026, 4:07 p.m.