Triple
T21980791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald Reagan Challenger disaster address |
E542832
|
entity |
| Predicate | timeAfterDisaster |
P146143
|
FINISHED |
| Object | same day as the Challenger explosion |
—
|
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: same day as the Challenger explosion | Statement: [Ronald Reagan Challenger disaster address, timeAfterDisaster, same day as the Challenger explosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeAfterDisaster Context triple: [Ronald Reagan Challenger disaster address, timeAfterDisaster, same day as the Challenger explosion]
-
A.
timePeriodOfMajorDestruction
Indicates the time span during which a major destructive event affecting the subject occurred.
-
B.
disasterDepicted
Indicates that one entity visually represents or portrays a disaster involving or affecting another entity.
-
C.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
D.
impactOfDisasters
Indicates the effects or consequences that disasters have on entities, conditions, or outcomes.
-
E.
populationAfterDestruction
Indicates the size or composition of a population following an event of destruction or devastation.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1248cf0388190b557d065beb662b5 |
completed | April 28, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69e6f6154e408190acc5b2c278acaff4 |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:04 p.m.