Triple
T36362
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badwater Basin |
E719
|
entity |
| Predicate | recordedTemperatureRegion |
P2974
|
FINISHED |
| Object | one of the hottest regions on Earth |
—
|
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 hottest regions on Earth | Statement: [Badwater Basin, recordedTemperatureRegion, one of the hottest regions on Earth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recordedTemperatureRegion Context triple: [Badwater Basin, recordedTemperatureRegion, one of the hottest regions on Earth]
-
A.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
B.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
C.
hasAverageSpringTemperature
Indicates that an entity is associated with a specific average temperature value measured over the spring season.
-
D.
regionName
Indicates the name assigned to a specific geographic or administrative region.
-
E.
locatedInTimeZone
Indicates that an entity exists or an event occurs within the temporal bounds defined by a specific time zone.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24bb753f081909cd8b25cfb8e08af |
completed | Feb. 28, 2026, 1:58 a.m. |
| PD | Predicate disambiguation | batch_69a24ab4a6908190b6f355415ffe7948 |
completed | Feb. 28, 2026, 1:53 a.m. |
| PDg | Predicate description generation | batch_69a24bb6881081909e7d650f2b3169d3 |
completed | Feb. 28, 2026, 1:58 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.