Triple
T834852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macondo |
E18046
|
entity |
| Predicate | climateInFiction |
P13811
|
FINISHED |
| Object | tropical |
—
|
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: tropical | Statement: [Macondo, climateInFiction, tropical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: climateInFiction Context triple: [Macondo, climateInFiction, tropical]
-
A.
climate
Indicates a relationship where environmental or atmospheric conditions influence, shape, or characterize something (such as a place, system, or process).
-
B.
climateChangeEffect
Indicates how climate change influences or alters a particular entity, condition, or process.
-
C.
climaticChallenge
Indicates a relationship where an entity faces, contributes to, or is affected by significant difficulties or stresses arising from climate or weather conditions.
-
D.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
-
E.
stateInFiction
chosen
Indicates that a particular state or condition exists within a fictional context or narrative world rather than in real-world actuality.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abccb94881909cd49aa3fd986b4a |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7c7df881909c539c3ab8ff0367 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.