Triple
T37738247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Officio |
E940635
|
entity |
| Predicate | widelyReadIn |
P184274
|
FINISHED |
| Object | Middle Ages |
—
|
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: Middle Ages | Statement: [De Officio, widelyReadIn, Middle Ages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: widelyReadIn Context triple: [De Officio, widelyReadIn, Middle Ages]
-
A.
isWidelyReadIn
chosen
Indicates that a work, author, or text is extensively read and commonly known within a particular region, community, or context.
-
B.
commonlyReadIn
Indicates that a work is frequently read within a particular location, community, or context.
-
C.
isWidelyReadBy
Indicates that a work (such as a book, article, or text) is read by a large and diverse number of people.
-
D.
readingOf
Indicates that one entity is an interpretation, measurement, or recorded value derived from another entity.
-
E.
alsoReadBy
Indicates that an item (such as a document, article, or book) has been read by another user or entity in addition to the primary one under consideration.
- 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_69f76ee0e32c8190b40a3b4cf590337c |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.