Triple
T13411543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muş |
E320098
|
entity |
| Predicate | hasHotDrySummers |
P21374
|
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: [Muş, hasHotDrySummers, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotDrySummers Context triple: [Muş, hasHotDrySummers, true]
-
A.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
-
B.
summerClimate
chosen
Indicates the typical weather conditions or characteristics that prevail in a place during the summer season.
-
C.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry season.
-
D.
hasLongWinterSeason
Indicates that the referenced entity experiences a winter season that lasts for an extended or unusually long period of time.
-
E.
summerHighTemperaturesOftenExceed
Indicates that during the summer season, the high temperatures in a given location frequently surpass a specified threshold.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:35 p.m.