Triple
T19980891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fair Youth |
E493812
|
entity |
| Predicate | conventionalNameFor |
P1354
|
FINISHED |
| Object | beautiful young man in Shakespeare’s sonnets |
—
|
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: beautiful young man in Shakespeare’s sonnets | Statement: [Fair Youth, conventionalNameFor, beautiful young man in Shakespeare’s sonnets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conventionalNameFor Context triple: [Fair Youth, conventionalNameFor, beautiful young man in Shakespeare’s sonnets]
-
A.
colloquialNameOf
Indicates that one entity is an informal, colloquial, or commonly used name referring to another entity.
-
B.
commonNameOf
chosen
Indicates that one entity is the commonly used or popular name by which the other entity is known.
-
C.
commonShortNameFor
Indicates that one entity is a commonly used short or abbreviated name for another entity.
-
D.
countrySpecificName
Indicates that an entity has a name or label that is specific to, or used within, a particular country.
-
E.
pairedTraditionalName
Indicates that two entities are associated as a traditional name pair, typically used together or in customary combination within a cultural or naming convention.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d12d968819081e315ec4585cd9f |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:28 p.m.