Triple
T30772773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parsabad |
E783570
|
entity |
| Predicate | hasHotDrySeason |
P189445
|
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, hasHotDrySeason, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotDrySeason Context triple: [Parsabad, hasHotDrySeason, true]
-
A.
hasDrySeasonCause
Indicates that one factor or condition is the underlying cause of a location or region experiencing a dry season.
-
B.
hasDrySeasonCapital
Indicates that a location serves as the capital or primary administrative center of a region specifically during the dry season.
-
C.
hasHotSeason
Indicates that an entity experiences a distinct period of time characterized by hot or high-temperature weather conditions.
-
D.
drySeason
Indicates that the relationship or action occurs during, or is characteristic of, a period with little or no rainfall.
-
E.
areaDrySeason
Indicates that the specified area experiences dry climatic conditions during the dry season.
- 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_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69fbc36bcac48190a726b40442c094d1 |
completed | May 6, 2026, 10:40 p.m. |
Created at: April 29, 2026, 8:40 p.m.