Triple
T2824967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Opera Ballet |
E54897
|
entity |
| Predicate | hasHierarchyRank |
P11443
|
FINISHED |
| Object | étoile |
—
|
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: étoile | Statement: [Paris Opera Ballet, hasHierarchyRank, étoile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHierarchyRank Context triple: [Paris Opera Ballet, hasHierarchyRank, étoile]
-
A.
hasHierarchyIn
Indicates that one entity occupies a higher or lower level within an ordered structure or chain of command relative to another entity in a specified context.
-
B.
isPartOfHierarchyWith
Indicates that one entity occupies a defined position within an ordered or nested structure relative to another entity in the same hierarchy.
-
C.
hasLegalHierarchy
Indicates that one entity holds a higher or subordinate legal status, authority, or jurisdiction in relation to another within a formal legal structure.
-
D.
legalHierarchyRank
Indicates the relative position or level of authority an entity holds within a legal or judicial hierarchy.
-
E.
hasRankCategory
chosen
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abdf15b7288190a03d1193cc0544a6 |
completed | March 7, 2026, 8:17 a.m. |
| PD | Predicate disambiguation | batch_69abdd08f2f481908c3da8a9c7a00552 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.