Triple
T27085315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swallow’s Nest |
E686020
|
entity |
| Predicate | hasConditionIssues |
P172228
|
FINISHED |
| Object | structural vulnerability due to cliff erosion |
—
|
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: structural vulnerability due to cliff erosion | Statement: [Swallow’s Nest, hasConditionIssues, structural vulnerability due to cliff erosion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConditionIssues Context triple: [Swallow’s Nest, hasConditionIssues, structural vulnerability due to cliff erosion]
-
A.
conditionIssues
chosen
Indicates that one entity has problems, defects, or concerns related to the state or condition of another entity.
-
B.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
C.
hadMultipleIssues
Indicates that the subject experienced more than one problem, error, or issue in the relevant context.
-
D.
hasTypicalConditions
Indicates that something is associated with conditions or circumstances that are commonly or normally present for it.
-
E.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
- 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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69feafa1ba0081909013800b85a9f613 |
completed | May 9, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69feae58d62c81909d031f3df8992883 |
completed | May 9, 2026, 3:47 a.m. |
Created at: April 27, 2026, 8:37 a.m.