Triple
T2010914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince |
E43685
|
entity |
| Predicate | usedSymbolName |
P2937
|
FINISHED |
| Object | unpronounceable love symbol |
—
|
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: unpronounceable love symbol | Statement: [Prince, usedSymbolName, unpronounceable love symbol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedSymbolName Context triple: [Prince, usedSymbolName, unpronounceable love symbol]
-
A.
usedSymbolInEmail
Indicates that a particular symbol was included or employed within the content of an email.
-
B.
hasSymbolNamedAfter
Indicates that one entity has a symbol whose name is derived from or dedicated to another entity.
-
C.
nameUsedIn
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
-
D.
nameUsedBy
chosen
Indicates that a particular name is employed or referenced by a specific entity.
-
E.
symbolicallyUses
Indicates that one entity employs another as a symbol or representation to convey meaning, ideas, or associations rather than for its literal or practical function.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b150a8819096c919465fd91ab5 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.