Triple
T31174233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Φ |
E794697
|
entity |
| Predicate | unicodeName |
P11609
|
FINISHED |
| Object | GREEK CAPITAL LETTER PHI |
—
|
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: GREEK CAPITAL LETTER PHI | Statement: [Φ, unicodeName, GREEK CAPITAL LETTER PHI]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: unicodeName Context triple: [Φ, unicodeName, GREEK CAPITAL LETTER PHI]
-
A.
hasUnicodeName
chosen
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
-
B.
UnicodeBlockName
Indicates the specific Unicode block to which a given character or code point belongs.
-
C.
UnicodeBlock
Indicates that a character belongs to a specific contiguous range of code points defined as a Unicode block.
-
D.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
-
E.
UnicodePlane
Indicates that a Unicode code point belongs to a specific Unicode plane (a contiguous range of code points grouped by plane number).
- 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_69f224d5b9708190b6ca79ad2fd3a28a |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69c234d648190a243fb2b107136a9 |
completed | May 3, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69f69665cd9c819088c388fc82fec42e |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 29, 2026, 9:07 p.m.