Triple
T22639482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Lebanon |
E558780
|
entity |
| Predicate | vexillologyCategory |
P58469
|
FINISHED |
| Object | flags with plants |
—
|
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: flags with plants | Statement: [Flag of Lebanon, vexillologyCategory, flags with plants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vexillologyCategory Context triple: [Flag of Lebanon, vexillologyCategory, flags with plants]
-
A.
vexillologicalCategory
chosen
Indicates the classification of something within a specific category or type used in the study of flags.
-
B.
vexillologyCode
Indicates a standardized code or classification assigned within the context of flags or the study of flags (vexillology).
-
C.
coatOfArms
Indicates that one entity serves as the heraldic emblem or coat of arms representing another entity.
-
D.
flagOrInsignia
Indicates that one entity serves as a flag, emblem, or insignia representing another entity.
-
E.
civilFlagDesign
Indicates the design or pattern used on the civil (non-state) version of a flag.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17010aa4c8190a9f0cf7eb4c066cd |
completed | April 29, 2026, 2:42 a.m. |
| PD | Predicate disambiguation | batch_69ee6294c4c08190b7e4829f4b9af24b |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:04 p.m.