Triple
T29007241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French press |
E736468
|
entity |
| Predicate | typicalWaterTemperatureCelsius |
P196689
|
FINISHED |
| Object | 90-96 |
—
|
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: 90-96 | Statement: [French press, typicalWaterTemperatureCelsius, 90-96]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWaterTemperatureCelsius Context triple: [French press, typicalWaterTemperatureCelsius, 90-96]
-
A.
typicalWaterTemperatureRange
chosen
Indicates the usual lower and upper bounds of water temperature typically associated with or experienced by an entity.
-
B.
typicalTemperature
Indicates the usual or characteristic temperature associated with an entity under normal conditions.
-
C.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
-
D.
waterTemperatureComparedTo
Indicates how the temperature of one body or sample of water compares to the temperature of another.
-
E.
hasAverageSummerWaterTemperature
Indicates that an entity is associated with a specific mean water temperature measured over the summer season.
- 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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a0149447e448190b0480943de0691ee |
completed | May 11, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_6a0148e2c39c8190a3ad6ea6be902c04 |
completed | May 11, 2026, 3:11 a.m. |
Created at: April 28, 2026, 9:39 a.m.