Triple
T4550308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DeSoto Falls |
E110145
|
entity |
| Predicate | hasSafetyConcern |
P30182
|
FINISHED |
| Object | slippery rocks near edges |
—
|
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: slippery rocks near edges | Statement: [DeSoto Falls, hasSafetyConcern, slippery rocks near edges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSafetyConcern Context triple: [DeSoto Falls, hasSafetyConcern, slippery rocks near edges]
-
A.
raisedConcernAbout
Indicates that one entity has expressed worry, doubt, or objection regarding another entity or issue.
-
B.
hasSecurityConsideration
Indicates that there is a relevant security-related issue, risk, or precaution associated with the referenced entity.
-
C.
observationSafety
Indicates that an observation or monitoring activity is conducted in a manner that ensures the safety of the subjects, observers, and environment involved.
-
D.
hasHealthConcern
Indicates that an entity has a specific health-related issue, condition, or concern associated with it.
-
E.
safetyRelevant
chosen
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f5a0a081909977ccbb8aba633c |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.