Triple
T30131522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Forest |
E765857
|
entity |
| Predicate | managementActionAfterAccident |
P180803
|
FINISHED |
| Object | bulldozing of dead trees |
—
|
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: bulldozing of dead trees | Statement: [Red Forest, managementActionAfterAccident, bulldozing of dead trees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: managementActionAfterAccident Context triple: [Red Forest, managementActionAfterAccident, bulldozing of dead trees]
-
A.
resultOfAccident
Indicates that something exists or occurs as a consequence or outcome of an accident.
-
B.
involvedInAccident
Indicates that an entity participated in, was affected by, or was otherwise a party to a specific accident or collision event.
-
C.
registrationStatusAfterAccident
Indicates the state of an entity’s registration following the occurrence of an accident.
-
D.
causedAccident
Indicates that one entity is responsible for bringing about or initiating an accident involving another entity or situation.
-
E.
accidentState
Indicates the condition or status of an accident at a given point in time.
- 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_69f22477d1a081908df2b7e6ed16859d |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
| PDg | Predicate description generation | batch_69f7516c538481908c6e55cf76add098 |
completed | May 3, 2026, 1:45 p.m. |
Created at: April 29, 2026, 7:15 p.m.