Triple
T22869894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harvard Classification Scheme |
E567162
|
entity |
| Predicate | temperatureOrder |
P150048
|
FINISHED |
| Object | O B A F G K M (hottest to coolest) |
—
|
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: O B A F G K M (hottest to coolest) | Statement: [Harvard Classification Scheme, temperatureOrder, O B A F G K M (hottest to coolest)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temperatureOrder Context triple: [Harvard Classification Scheme, temperatureOrder, O B A F G K M (hottest to coolest)]
-
A.
temperatureOrderOfMagnitude
Indicates that the temperatures of the related entities differ by approximately a specified order of magnitude (i.e., by a power-of-ten scale factor).
-
B.
temperatureConditions
Indicates the specific thermal or weather-related temperature state or range affecting an entity or situation.
-
C.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
-
D.
seasonalOrder
Indicates the temporal ordering of events or states according to their position within a recurring seasonal cycle.
-
E.
hasTemperature
Indicates that an entity possesses or is characterized by a specific temperature value.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f0384a88190a0fbf57b5dca8d5a |
completed | April 29, 2026, 3:46 a.m. |
| PD | Predicate disambiguation | batch_69eed2d8c0608190afef4c4e530c0e2c |
completed | April 27, 2026, 3:07 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:38 p.m.