Triple
T22110143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIP |
E546390
|
entity |
| Predicate | containsCharactersBeyondBMP |
P132526
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [SIP, containsCharactersBeyondBMP, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsCharactersBeyondBMP Context triple: [SIP, containsCharactersBeyondBMP, true]
-
A.
hasBlockUnicode
Indicates that one entity possesses or is associated with a specific Unicode block related to another entity.
-
B.
hasNumberOfBasicCharacters
Indicates the quantity of basic (non-accented or fundamental) characters associated with an entity.
-
C.
hasAdditionalUnicodeBlock
Indicates that an entity is associated with one or more supplementary Unicode character blocks beyond its primary assigned block.
-
D.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
-
E.
usesSurrogatePairs
chosen
Indicates that a string or text representation encodes certain characters using Unicode surrogate pairs rather than single code units.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12948c2ec819083340787b2062649 |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:30 p.m.