Triple
T3480852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana Gulf Coast |
E73485
|
entity |
| Predicate | hasNotableEventType |
P18677
|
FINISHED |
| Object | hurricane landfall |
—
|
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: hurricane landfall | Statement: [Louisiana Gulf Coast, hasNotableEventType, hurricane landfall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableEventType Context triple: [Louisiana Gulf Coast, hasNotableEventType, hurricane landfall]
-
A.
hasNotableResponse
Indicates that an entity has received a significant, noteworthy, or widely recognized reaction or feedback in response to it.
-
B.
hasNotableIssue
Indicates that an entity is associated with a significant problem, concern, or defect that is noteworthy or exceptional compared to typical cases.
-
C.
hasNotableType
Indicates that an entity is associated with a specific notable category or type that characterizes its significance or role.
-
D.
hasNotableIncident
chosen
Indicates that an entity is associated with a significant or noteworthy event, occurrence, or incident.
-
E.
hasEventType
Indicates that an event is associated with, or classified under, a specific type or category of event.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb75850c8190ad02cf2bde8be8a7 |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:17 p.m.