Triple
T29750120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French military hierarchy |
E752869
|
entity |
| Predicate | includesRankCategory |
P201507
|
FINISHED |
| Object | officiers généraux |
—
|
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: officiers généraux | Statement: [French military hierarchy, includesRankCategory, officiers généraux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesRankCategory Context triple: [French military hierarchy, includesRankCategory, officiers généraux]
-
A.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
B.
hasRankingCategory
Indicates that an entity is associated with a particular ranking category or tier within an ordered classification system.
-
C.
containsRank
Indicates that one entity includes or encompasses another entity that has a specific rank or hierarchical level within it.
-
D.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
-
E.
rankCategoryBetween
Indicates that an entity’s rank or classification falls within a specified range between two rank categories.
- 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fffc783b648190bcd7df017514d206 |
completed | May 10, 2026, 3:33 a.m. |
| PD | Predicate disambiguation | batch_69fffc03fa24819099e12413dc6e0afd |
completed | May 10, 2026, 3:31 a.m. |
| PDg | Predicate description generation | batch_69fffc7793bc81908d7b41eeec42c2f2 |
completed | May 10, 2026, 3:33 a.m. |
Created at: April 28, 2026, 7:53 p.m.