Triple
T67236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Légion d'honneur |
E1340
|
entity |
| Predicate | highestRankIn |
P4202
|
FINISHED |
| Object | French system of orders, decorations and medals |
—
|
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 system of orders, decorations and medals | Statement: [Légion d'honneur, highestRankIn, French system of orders, decorations and medals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: highestRankIn Context triple: [Légion d'honneur, highestRankIn, French system of orders, decorations and medals]
-
A.
rankedAs
Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
-
B.
depthRank
Indicates the relative ordering of entities based on how deep or distant they are along a specified depth dimension or hierarchy.
-
C.
peakOutputRanking
Indicates the relative position of an entity in an ordered list based on its maximum or peak output level.
-
D.
isSecondHighest
Indicates that one entity ranks immediately below the highest-ranked entity within a specified ordering or set.
-
E.
honorificRank
Indicates that one entity holds a formal title or honorific status in relation to another entity.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2509b5a088190bb9d2b650aeb8bca |
completed | Feb. 28, 2026, 2:19 a.m. |
| PD | Predicate disambiguation | batch_69a24ea749788190bc17865171ff909a |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2509a1c088190b4afa3045455709a |
completed | Feb. 28, 2026, 2:19 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.