Triple
T16284405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giulia |
E395350
|
entity |
| Predicate | hasMeaningNote |
P10718
|
FINISHED |
| Object | shares roots with names meaning "youthful" via Julius |
—
|
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: shares roots with names meaning "youthful" via Julius | Statement: [Giulia, hasMeaningNote, shares roots with names meaning "youthful" via Julius]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeaningNote Context triple: [Giulia, hasMeaningNote, shares roots with names meaning "youthful" via Julius]
-
A.
hasMultipleMeanings
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
B.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
-
C.
possibleMeaning
chosen
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
D.
hasMeaningViaJohn
Indicates that something possesses or conveys its meaning specifically through John as the interpretive or mediating agent.
-
E.
hasDisambiguationNote
Indicates that there is an explanatory note used to distinguish this entity or term from other entities or terms with similar or identical names.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24912c5808190a0d9c9f491315068 |
completed | April 17, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:05 a.m.