Triple
T12228352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emblem of Hong Kong |
E291410
|
entity |
| Predicate | flowerColorMeaning |
P24024
|
FINISHED |
| Object | distinct identity of Hong Kong within China |
—
|
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: distinct identity of Hong Kong within China | Statement: [Emblem of Hong Kong, flowerColorMeaning, distinct identity of Hong Kong within China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: flowerColorMeaning Context triple: [Emblem of Hong Kong, flowerColorMeaning, distinct identity of Hong Kong within China]
-
A.
flowerSymbolMeaning
chosen
Indicates that a particular flower is used to represent or convey a specific symbolic meaning or message.
-
B.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
C.
flowerType
Indicates the specific kind or category of flower associated with an entity.
-
D.
hasFlowerColor
Indicates that an entity (typically a plant or flower) possesses a specific flower color.
-
E.
flowerCharacteristic
Indicates that a flower possesses a particular attribute, quality, or feature (such as color, shape, size, or scent).
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.