Triple
T31016247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unit 3 reactor building |
E790333
|
entity |
| Predicate | explosionEffect |
P173429
|
FINISHED |
| Object | severe structural damage to upper floors |
—
|
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: severe structural damage to upper floors | Statement: [Unit 3 reactor building, explosionEffect, severe structural damage to upper floors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: explosionEffect Context triple: [Unit 3 reactor building, explosionEffect, severe structural damage to upper floors]
-
A.
explosionType
Indicates the specific kind or category of explosion associated with an event or entity.
-
B.
explosionOccurred
Indicates that an explosion event has taken place at a specific time and/or location.
-
C.
explosionDesignation
Indicates that an entity is assigned a specific designation or label associated with an explosion event or explosive classification.
-
D.
fireEffect
Indicates that one entity produces, causes, or is associated with a fire-related impact or consequence on another entity.
-
E.
explosionMechanism
Indicates the specific process or mechanism by which an explosion is initiated or occurs.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6b56ed31481908c3e5d749e46bad9 |
completed | May 3, 2026, 2:39 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a7bdb481908d16a32f49e38c2c |
completed | May 3, 2026, 2:32 a.m. |
| PDg | Predicate description generation | batch_69f6b49339048190b617a6749f648825 |
completed | May 3, 2026, 2:36 a.m. |
Created at: April 29, 2026, 8:57 p.m.