Triple
T3657849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Vie Claire |
E77575
|
entity |
| Predicate | hadNationalityMix |
P50177
|
FINISHED |
| Object | French and American leaders |
—
|
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: French and American leaders | Statement: [La Vie Claire, hadNationalityMix, French and American leaders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadNationalityMix Context triple: [La Vie Claire, hadNationalityMix, French and American leaders]
-
A.
hasNationalityTraditionally
Indicates that an entity is traditionally or historically associated with a particular nationality, regardless of current legal or formal citizenship status.
-
B.
includedNationality
Indicates that one entity’s set of nationalities contains or encompasses the nationality of another entity.
-
C.
hasEthnicallyMixedPopulation
Indicates that a population is composed of people from multiple distinct ethnic groups rather than being ethnically homogeneous.
-
D.
nationalityInText
Indicates that a person's nationality is mentioned or specified within a given text.
-
E.
nationalityInHumanWorld
Indicates that one entity has the specified national affiliation or citizenship within the context of the human world.
- 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_69ad85def5cc8190863dccf55a18bebb |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc3d36c1c8190920397a75de4c47d |
completed | March 8, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69adb847e9d881909dad2ffd0f3b6c15 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb97cdb788190a5ce96b21bd157ab |
completed | March 8, 2026, 6:01 p.m. |
Created at: March 8, 2026, 3:24 p.m.