Triple
T15284846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Camille |
E365366
|
entity |
| Predicate | rankAmongUSLandfallsByPressure |
P117953
|
FINISHED |
| Object | one of the lowest on record |
—
|
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: one of the lowest on record | Statement: [Hurricane Camille, rankAmongUSLandfallsByPressure, one of the lowest on record]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankAmongUSLandfallsByPressure Context triple: [Hurricane Camille, rankAmongUSLandfallsByPressure, one of the lowest on record]
-
A.
rankByAtlanticHurricaneIntensity
Indicates the ordering of entities based on the strength or severity of Atlantic hurricanes associated with them.
-
B.
rankAmongDeadliestCyclones
Indicates how a cyclone is positioned or ordered in terms of its deadliness relative to other cyclones.
-
C.
lowestCentralPressure_inHg
Indicates the minimum central atmospheric pressure of a system, measured in inches of mercury (inHg).
-
D.
strongestStorm
Indicates that one storm is the most intense or powerful compared to a set of other storms.
-
E.
numberOfNamedStorms
Indicates the total count of distinct storms that have been formally assigned names within a specified context or period.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e53c9588190a6cb61ac8805c706 |
completed | April 15, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69deca90739081909bd1b797cdb8af2b |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:15 a.m.