Triple
T8124420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treaty of Sugauli |
E189687
|
entity |
| Predicate | effectOnSubject |
P53074
|
FINISHED |
| Object | significant reduction of Nepalese territory |
—
|
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: significant reduction of Nepalese territory | Statement: [Treaty of Sugauli, effectOnSubject, significant reduction of Nepalese territory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnSubject Context triple: [Treaty of Sugauli, effectOnSubject, significant reduction of Nepalese territory]
-
A.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
B.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
-
C.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
D.
eventEffect
chosen
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
E.
effectControlledBy
Indicates that the occurrence, magnitude, or outcome of one effect is regulated, determined, or constrained by another specified factor or agent.
- 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_69ca82bb74848190afb1f18640632c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4c4c2e388190b86854f8b1765e61 |
completed | March 31, 2026, 4:23 a.m. |
| PD | Predicate disambiguation | batch_69cb3696379c8190a20965e59ed8f370 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:34 p.m.