Triple
T2157721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gutenberg Bible copies |
E47929
|
entity |
| Predicate | haveRubrication |
P22465
|
FINISHED |
| Object | red and blue initials |
—
|
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: red and blue initials | Statement: [Gutenberg Bible copies, haveRubrication, red and blue initials]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveRubrication Context triple: [Gutenberg Bible copies, haveRubrication, red and blue initials]
-
A.
followsRubricsOf
Indicates that one entity adheres to, complies with, or operates according to the rules, guidelines, or evaluation criteria defined by another entity.
-
B.
hasColoration
chosen
Indicates that an entity possesses a particular color or pattern of colors.
-
C.
hasScutes
Indicates that an entity possesses scutes, meaning it has bony or horny external plates as part of its body covering.
-
D.
hasLuster
Indicates that one entity possesses a shiny, glossy, or reflective surface quality.
-
E.
hasTissue
Indicates that one entity possesses, contains, or is associated with a specific tissue of another entity.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe68fe0c8190beb5db003738a6e5 |
completed | March 7, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69abbd9a60648190b20b116be5c7ad98 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.