Triple
T10786339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Unicode 7.0 |
E254460
|
entity |
| Predicate | totalCharactersInStandard |
P95475
|
FINISHED |
| Object | 113021 |
—
|
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: 113021 | Statement: [Unicode 7.0, totalCharactersInStandard, 113021]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalCharactersInStandard Context triple: [Unicode 7.0, totalCharactersInStandard, 113021]
-
A.
numberOfCharacters
Indicates the total count of individual characters present in a given text, string, or entity’s representation.
-
B.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
-
C.
totalCharactersAfterRelease
Indicates the total number of characters that exist in a work or product after its release (including any additions or updates made post-launch).
-
D.
numberOfPlayableCharacters
Indicates the total count of distinct characters that can be actively controlled or played by a user in a game or interactive experience.
-
E.
numberOfCommonUseCharacters
Indicates the count of characters that are shared in common between two entities’ representations or strings.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69d6fa334b8c819082eaf8537084c323 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:17 p.m.