Triple
T7847068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | multilateral development banks |
E181948
|
entity |
| Predicate | haveSafeguardsFor |
P20171
|
FINISHED |
| Object | environmental impacts |
—
|
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: environmental impacts | Statement: [multilateral development banks, haveSafeguardsFor, environmental impacts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveSafeguardsFor Context triple: [multilateral development banks, haveSafeguardsFor, environmental impacts]
-
A.
safeguardingMeasuresInclude
Indicates that certain specific protective or security measures are contained within, or form part of, a broader set of safeguarding measures.
-
B.
safeguard
Indicates taking protective actions to shield someone or something from harm, loss, or danger.
-
C.
securityGuarantee
Indicates a commitment by one party to protect or defend another party against specified threats or risks.
-
D.
protectionMeasures
Indicates actions or safeguards implemented to prevent harm, damage, or risk to someone or something.
-
E.
providesProtectionAgainst
chosen
Indicates that one entity serves to guard, shield, or defend another entity from a specified harm, threat, or adverse effect.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb164105fc8190a60aaa27dd619d5a |
completed | March 31, 2026, 12:33 a.m. |
| PD | Predicate disambiguation | batch_69cae92180f88190ae3d44c3de7adc93 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:49 p.m.