Triple
T31823842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Princess Hildegard |
E812338
|
entity |
| Predicate | fellowStudentWith |
P11805
|
FINISHED |
| Object | Princess Amber |
—
|
NE NERFINISHED |
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: Princess Amber | Statement: [Princess Hildegard, fellowStudentWith, Princess Amber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fellowStudentWith Context triple: [Princess Hildegard, fellowStudentWith, Princess Amber]
-
A.
notableStudentOrColleague
Indicates that one entity is a notable student or professional colleague of another entity.
-
B.
studiedAlongWith
chosen
Indicates that two or more entities engaged in studying the same subject or course together during the same time period.
-
C.
notableStudentOrFollower
Indicates that one entity is a notable student or follower of another entity, highlighting a significant mentor–disciple or influence relationship between them.
-
D.
studentOrTeacherOf
Indicates that one entity is either a student of, or a teacher of, another entity within some educational or instructional context.
-
E.
collegeTeammateOf
Indicates that two individuals were teammates on the same college sports team.
- 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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6af8130148190834cca27b2458735 |
completed | May 3, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 30, 2026, 11:46 p.m.