Triple
T14408778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Codex Egberti |
E357269
|
entity |
| Predicate | approximateFolioCount |
P114136
|
FINISHED |
| Object | about 165 folios |
—
|
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: about 165 folios | Statement: [Codex Egberti, approximateFolioCount, about 165 folios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateFolioCount Context triple: [Codex Egberti, approximateFolioCount, about 165 folios]
-
A.
sectionCountApproximate
Indicates that the number of sections associated with an entity is known only approximately rather than as an exact count.
-
B.
sectorCountApprox
Indicates that the number of sectors involved is an approximate or estimated count rather than an exact value.
-
C.
numberOfHoldings
Indicates the quantity of distinct holdings or assets associated with an entity.
-
D.
hasApproximateNumberOfResponsa
Indicates that an entity is associated with a rough or estimated count of responsa, rather than an exact number.
-
E.
articleCountApprox
Indicates that the relationship specifies an approximate number of articles associated with an entity.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90c7a068819081b4b516983a1412 |
completed | April 14, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69de2aa1b57881909a033eac8545c417 |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e08b6c08190bb4c929deab236a6 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:17 a.m.