Triple
T16641099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Not Fair |
E404338
|
entity |
| Predicate | featuresCountryInfluence |
P32644
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Not Fair, featuresCountryInfluence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCountryInfluence Context triple: [Not Fair, featuresCountryInfluence, true]
-
A.
featuresCountry
chosen
Indicates that something includes, highlights, or prominently involves a particular country.
-
B.
hasRegionalInfluenceFrom
Indicates that one entity’s influence, impact, or authority in a region is derived from or shaped by another entity.
-
C.
influencesRegion
Indicates that one entity has an effect on, shapes, or alters the conditions, characteristics, or behavior of a specified region.
-
D.
placeOfInfluence
Indicates the location or area where an entity exerts significant impact, authority, or cultural, social, or intellectual influence.
-
E.
countrySignificance
Indicates the degree of importance, influence, or relevance that one country holds in relation to another entity or context.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad1a7748190aa9308d4e96c566c |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e296af2f88819092c9ffee4a65d7dd |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:18 a.m.