Triple
T1457267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaziranga National Park |
E31425
|
entity |
| Predicate | facingThreats |
P956
|
FINISHED |
| Object | flooding |
—
|
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: flooding | Statement: [Kaziranga National Park, facingThreats, flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facingThreats Context triple: [Kaziranga National Park, facingThreats, flooding]
-
A.
threatenedBy
chosen
Indicates that one entity poses a danger or potential harm to another entity.
-
B.
endangerment
Indicates a relationship in which one entity exposes another to potential harm, risk, or danger.
-
C.
primaryThreat
Indicates that one entity is the main or most significant source of danger, harm, or risk to another entity.
-
D.
opposingForce
Indicates a relationship where one entity actively resists, counters, or works against the actions, goals, or influence of another entity.
-
E.
aimsToProtect
Indicates an intention or purpose to safeguard or defend one entity, value, or condition from harm, risk, or undesirable outcomes.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c598b30c8190b87207adf608b89a |
completed | March 1, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69a4c47ec5108190b1772237f2e5d90b |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.