Triple
T10786341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 7.0 |
E254460
|
entity |
| Predicate | addsEmojiCharacters |
P47138
|
FINISHED |
| Object | many new emoji symbols |
—
|
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: many new emoji symbols | Statement: [Unicode 7.0, addsEmojiCharacters, many new emoji symbols]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addsEmojiCharacters Context triple: [Unicode 7.0, addsEmojiCharacters, many new emoji symbols]
-
A.
addsEmoji
Indicates that one entity appends or includes an emoji in relation to another entity or piece of content.
-
B.
addsEmojiCharactersCount
chosen
Indicates that an action or process increases the number of emoji characters present in some content or text.
-
C.
includesEmoji
Indicates that the related content contains at least one emoji character.
-
D.
addsEmojiSequencesCount
Indicates that an entity increases the number of emoji sequences associated with another entity or context.
-
E.
addsEmojiZwjSequencesCount
Indicates that an entity increases the number of emoji sequences formed using Zero Width Joiner (ZWJ) combinations.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d44b488190a9f3ab9b177e737a |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.