Triple
T35007803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess of Tamaran |
E1009858
|
entity |
| Predicate | notableBearerGender |
P162146
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Princess of Tamaran, notableBearerGender, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableBearerGender Context triple: [Princess of Tamaran, notableBearerGender, female]
-
A.
notableBearerNationality
Indicates that the subject has a notable bearer whose nationality is the specified object.
-
B.
notableBearerFullName
Indicates that a full personal name is that of a notable or well-known bearer associated with the referenced entity.
-
C.
notableBearerPersonality
Indicates that the person who notably bears or holds something does so with a particular personality, character, or behavioral style.
-
D.
bearerGender
chosen
Indicates the gender associated with the bearer in the relationship or context.
-
E.
notableBearerEthnicity
Indicates that the notable person bearing something (such as a name, title, or role) belongs to a specified ethnic group.
- 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_69f76dcb716881909f75e4fd60ab2284 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:01 p.m.