Triple
T24379479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Codex |
E614568
|
entity |
| Predicate | sisterCodex |
P155988
|
FINISHED |
| Object | Dresden Codex |
—
|
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: Dresden Codex | Statement: [Paris Codex, sisterCodex, Dresden Codex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sisterCodex Context triple: [Paris Codex, sisterCodex, Dresden Codex]
-
A.
sisterScript
Indicates that two writing systems are closely related variants derived from a common ancestral script or design.
-
B.
sisterBase
Indicates that one entity is the sister of another, sharing at least one parent and being female relative to the other entity.
-
C.
sisterComplex
Indicates a strong, often excessive or romanticized emotional fixation or attraction that someone has toward their sister.
-
D.
sisterPillar
Indicates a relationship where one pillar is considered the sister (a closely related or counterpart structure) to another pillar.
-
E.
sisterModule
Indicates that two modules share a common parent or grouping, making them parallel or peer components within the same larger structure.
- F. None of above. chosen
Provenance (4 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_69e2d7e362e481909e32fe4ef8269d4f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293da489c81909a7912b790be8b8a |
completed | April 29, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:02 a.m.