Triple
T7206570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GATT dispute settlement system |
E148679
|
entity |
| Predicate | enforcementStrength |
P75822
|
FINISHED |
| Object | relatively weak |
—
|
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: relatively weak | Statement: [GATT dispute settlement system, enforcementStrength, relatively weak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enforcementStrength Context triple: [GATT dispute settlement system, enforcementStrength, relatively weak]
-
A.
enforcement
Indicates the act of compelling compliance with rules, laws, or agreements through monitoring, pressure, or sanctions.
-
B.
estimatedStrength
Indicates that a value represents an approximate or inferred level, magnitude, or intensity of something rather than a precisely measured strength.
-
C.
enforcedOn
Indicates that a rule, policy, or constraint is applied with authority to a particular target or subject.
-
D.
enforcedLaw
Indicates that an authority actively applies or upholds a specific law to regulate behavior or resolve situations.
-
E.
lawEnforcementLevel
Indicates the degree or intensity of law enforcement presence, activity, or strictness applied in a given context.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94ef5cc81908c33adcedf5c5054 |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8fd9b848190b2b1beea5698422b |
completed | March 27, 2026, 8:30 p.m. |
Created at: March 27, 2026, 2:52 p.m.