Triple
T13816173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Prince |
E332024
|
entity |
| Predicate | oftenGivenNameIn |
P19169
|
FINISHED |
| Object | modern adaptations |
—
|
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: modern adaptations | Statement: [the Prince, oftenGivenNameIn, modern adaptations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenGivenNameIn Context triple: [the Prince, oftenGivenNameIn, modern adaptations]
-
A.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
-
B.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
C.
givenNameFor
Indicates that one entity is the personal first name assigned to or used for another entity.
-
D.
isAmongMostCommonSurnamesIn
Indicates that a surname ranks within the group of most frequently occurring surnames in a specified region or population.
-
E.
isCommonAsFirstName
chosen
Indicates that the referenced name is frequently used as a first (given) name within a specified population or context.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02806e148190996f58934e66d7d8 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.