Triple
T3006049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombay Beach, California |
E81903
|
entity |
| Predicate | hasWinterTemperatureCharacteristic |
P10789
|
FINISHED |
| Object | mild winters |
—
|
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: mild winters | Statement: [Bombay Beach, California, hasWinterTemperatureCharacteristic, mild winters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWinterTemperatureCharacteristic Context triple: [Bombay Beach, California, hasWinterTemperatureCharacteristic, mild winters]
-
A.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
-
B.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
C.
requiresEquipmentInWinter
Indicates that performing the related activity or fulfilling the related condition necessitates the use of specific equipment during winter.
-
D.
winterCharacteristic
chosen
Indicates a characteristic, feature, or quality that is specifically associated with or typical of winter.
-
E.
wintersIn
Indicates that an entity spends the winter season in a particular place or region.
- 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_69ad8b1c4de88190a83b7cefaa1f2842 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a48f0888190bdec150dac623851 |
completed | March 8, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69ad96180eb08190a524c5f458d41382 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.