Triple
T14200263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Djibouti |
E351944
|
entity |
| Predicate | laurelWreathMeaning |
P77716
|
FINISHED |
| Object | victory |
—
|
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: victory | Statement: [Coat of arms of Djibouti, laurelWreathMeaning, victory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laurelWreathMeaning Context triple: [Coat of arms of Djibouti, laurelWreathMeaning, victory]
-
A.
wreathMeaning
chosen
Indicates that one entity is a wreath that symbolizes, represents, or conveys a particular meaning, theme, or sentiment associated with another entity.
-
B.
ribbonMeaning
Indicates that one entity symbolically represents, commemorates, or raises awareness for a cause, event, or concept through the use of a ribbon.
-
C.
wreathType
Indicates the specific kind or category of wreath associated with an entity.
-
D.
wreathColor
Indicates the color associated with a given wreath.
-
E.
wreathComponents
Indicates that one or more items serve as constituent parts or materials that make up a wreath.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f472548190a1a7edc40526eac3 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:04 a.m.