Triple
T14695935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airborne Toxic Event |
E345158
|
entity |
| Predicate | effectOnCharacters |
P58916
|
FINISHED |
| Object | mass evacuation |
—
|
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: mass evacuation | Statement: [Airborne Toxic Event, effectOnCharacters, mass evacuation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnCharacters Context triple: [Airborne Toxic Event, effectOnCharacters, mass evacuation]
-
A.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
B.
effectOnOthers
chosen
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
influencesCharacter
Indicates that one entity affects, shapes, or alters the traits, behavior, or development of another entity’s character.
-
D.
targetsCharacter
Indicates that one entity is the intended focus or target of another entity’s action, effect, or behavior.
-
E.
effectOnSpelling
Indicates a relationship where one factor influences or alters the way something is spelled.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb58855e081908b38f9515db5677f |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.