Triple
T1413990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Storrow Drive |
E31868
|
entity |
| Predicate | hasLocalIssue |
P13650
|
FINISHED |
| Object | periodic flooding in heavy rain |
—
|
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: periodic flooding in heavy rain | Statement: [Storrow Drive, hasLocalIssue, periodic flooding in heavy rain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalIssue Context triple: [Storrow Drive, hasLocalIssue, periodic flooding in heavy rain]
-
A.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
B.
hasTargetIssue
Indicates that an entity is associated with or directed toward a specific issue, problem, or concern as its focus.
-
C.
hasKeyIssue
Indicates that an entity is associated with a primary or central problem, concern, or topic of importance.
-
D.
facingIssue
chosen
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
-
E.
raisesIssue
Indicates that one entity brings up, reports, or formally submits a concern, problem, or topic for attention to another entity or system.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3e476f08190aed1576805c62462 |
completed | March 1, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69a4bf060b0081909ba00e6ac093a28b |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.