Triple
T7439245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ordre de la Libération |
E171702
|
entity |
| Predicate | insigniaObverseDesign |
P1602
|
FINISHED |
| Object | sword and Cross of Lorraine |
—
|
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: sword and Cross of Lorraine | Statement: [Ordre de la Libération, insigniaObverseDesign, sword and Cross of Lorraine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: insigniaObverseDesign Context triple: [Ordre de la Libération, insigniaObverseDesign, sword and Cross of Lorraine]
-
A.
insigniaCaption
Indicates the text that serves as a caption or explanatory label specifically for an insignia.
-
B.
insigniaName
Indicates the specific name or designation assigned to an insignia associated with an entity.
-
C.
obverseDepiction
Indicates that one entity is depicted on the obverse (front) side of another, such as the front face of a coin or medal.
-
D.
badgeObverseDesign
chosen
Indicates the design or imagery that appears on the front (obverse) side of a badge.
-
E.
obverseDesignIntroduced
Indicates that a particular obverse design (front side of an item, typically a coin or medal) was first put into official use at a specified time.
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34c28648190a426b5d7623b41e8 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:13 p.m.