Triple
T30772772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parsabad |
E783570
|
entity |
| Predicate | hasColdSeasonPrecipitation |
P203504
|
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: [Parsabad, hasColdSeasonPrecipitation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColdSeasonPrecipitation Context triple: [Parsabad, hasColdSeasonPrecipitation, true]
-
A.
hasWinterPhenomenon
Indicates that an entity experiences or is characterized by a particular phenomenon occurring during the winter season.
-
B.
hasSeasonalSnowCover
Indicates that an entity is covered by snow during certain seasons or periods of the year, rather than permanently.
-
C.
hasWinterSeason
Indicates that an entity experiences or includes a distinct winter season within its annual climate or temporal cycle.
-
D.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
-
E.
hasSnowClimate
Indicates that a location or region experiences a climate characterized by regular or significant snowfall.
- 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_69f224b1519081908b9db003fd2073e0 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a01926e2f348190a632eff5c91db5e0 |
completed | May 11, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_6a01923488f4819094d79a27f4bc8ab8 |
completed | May 11, 2026, 8:24 a.m. |
| PDg | Predicate description generation | batch_6a01926d10988190b6fbf03866337860 |
completed | May 11, 2026, 8:25 a.m. |
Created at: April 29, 2026, 8:40 p.m.