Triple
T38412968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tateyama, Chiba |
E901526
|
entity |
| Predicate | hasWarmSummers |
P192962
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Tateyama, Chiba, hasWarmSummers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWarmSummers Context triple: [Tateyama, Chiba, hasWarmSummers, true]
-
A.
hasMildSummers
Indicates that a place experiences relatively cool or moderate summer temperatures rather than hot or extreme heat.
-
B.
hasWarmerWintersThan
Indicates that the typical winter temperatures in one entity are higher than those in another entity.
-
C.
hasHotDrySeason
Indicates that a place experiences a distinct period characterized by hot and dry climatic conditions.
-
D.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
-
E.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
- 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_69f76e61e79c81908b787d83b46ab92b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69fd328298ac8190b6bd5ded7dca270d |
completed | May 8, 2026, 12:46 a.m. |
Created at: May 3, 2026, 4:31 p.m.