Triple
T191016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officier de la Légion d'honneur |
E3720
|
entity |
| Predicate | insigniaShape |
P1464
|
FINISHED |
| Object | five-armed Maltese asterisk star |
—
|
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: five-armed Maltese asterisk star | Statement: [Officier de la Légion d'honneur, insigniaShape, five-armed Maltese asterisk star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: insigniaShape Context triple: [Officier de la Légion d'honneur, insigniaShape, five-armed Maltese asterisk star]
-
A.
badgeShape
Indicates the geometric form or outline that a badge takes.
-
B.
shape
chosen
Indicates that one entity has a particular geometric or physical form characterized by the other entity.
-
C.
shaped
Indicates that one entity has given form, contour, or structure to another entity or outcome.
-
D.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
E.
leafShape
Indicates the characteristic form or outline of a leaf that an entity possesses or exhibits.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.