Triple
T35922884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Francis Dam disaster |
E1038932
|
entity |
| Predicate | distanceFloodTraveled |
P16230
|
FINISHED |
| Object | about 54 miles |
—
|
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 54 miles | Statement: [St. Francis Dam disaster, distanceFloodTraveled, about 54 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFloodTraveled Context triple: [St. Francis Dam disaster, distanceFloodTraveled, about 54 miles]
-
A.
distanceTraveled
chosen
Indicates the total length of the path an entity has moved over a period of time or between two points.
-
B.
distanceChange
Indicates a change in the spatial distance between two entities over time.
-
C.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
D.
distanceToFidra
Indicates the spatial distance between a given entity and the reference location Fidra.
-
E.
distanceChangedTo
Indicates that the distance between two entities has been updated from a previous value to a new specified value.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:07 p.m.