Triple
T28271251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jardines de la Reina |
E712858
|
entity |
| Predicate | globalThreats |
P164226
|
FINISHED |
| Object | climate change |
—
|
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: climate change | Statement: [Jardines de la Reina, globalThreats, climate change]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: globalThreats Context triple: [Jardines de la Reina, globalThreats, climate change]
-
A.
threatsFaced
Indicates that an entity is exposed to or experiences specific dangers, risks, or harmful conditions.
-
B.
targetsThreat
Indicates that one entity is directing an action or focus specifically toward a perceived threat.
-
C.
laterThreat
Indicates that one entity poses a threat to another at a time subsequent to some referenced or initial point.
-
D.
facesThreat
Indicates that an entity is exposed to or confronted by a potential danger, risk, or harmful situation.
-
E.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64447b738819088589cca5312c4e8 |
completed | May 2, 2026, 6:36 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
| PDg | Predicate description generation | batch_69f6430975b481909191219ad13ef77e |
completed | May 2, 2026, 6:31 p.m. |
Created at: April 27, 2026, 11:17 p.m.