Triple
T32551252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Johnstown Flood of 1889 |
E831977
|
entity |
| Predicate | timeToReachTown |
P174918
|
FINISHED |
| Object | about 57 minutes after dam failure |
—
|
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 57 minutes after dam failure | Statement: [Great Johnstown Flood of 1889, timeToReachTown, about 57 minutes after dam failure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToReachTown Context triple: [Great Johnstown Flood of 1889, timeToReachTown, about 57 minutes after dam failure]
-
A.
timeToReachNearKhartoum
Indicates the amount of time required for an entity to arrive at or near the location of Khartoum.
-
B.
timeOfJourneyDescribed
Indicates that the predicate specifies the particular time period or duration during which the described journey takes place.
-
C.
distanceToRailhead
Indicates the measured distance between a location or object and the nearest railhead (rail transport access point).
-
D.
approximateDrivingTime
Indicates the estimated amount of time it takes to drive from one location to another under typical conditions.
-
E.
distanceTraveled
Indicates the total length of the path an entity has moved over a period of time or between two points.
- 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c90790788190a1ed09adc86ed22d |
completed | May 3, 2026, 4:03 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c814c26c81908f5c47285129ff2a |
completed | May 3, 2026, 3:59 a.m. |
Created at: May 1, 2026, 1:02 a.m.