Triple
T2917138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nawabshah |
E78632
|
entity |
| Predicate | hasHotSeason |
P43888
|
FINISHED |
| Object | summer temperatures often above 45°C |
—
|
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: summer temperatures often above 45°C | Statement: [Nawabshah, hasHotSeason, summer temperatures often above 45°C]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotSeason Context triple: [Nawabshah, hasHotSeason, summer temperatures often above 45°C]
-
A.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
B.
hasSeasonType
Indicates that something is associated with a particular category or type of season (e.g., summer, winter, rainy).
-
C.
hasSeasonalStatus
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
D.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
-
E.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:53 p.m.