Triple
T20320943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disputation of Paris |
E492203
|
entity |
| Predicate | numberOfManuscriptsBurned |
P20104
|
FINISHED |
| Object | thousands of Hebrew manuscripts |
—
|
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: thousands of Hebrew manuscripts | Statement: [Disputation of Paris, numberOfManuscriptsBurned, thousands of Hebrew manuscripts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfManuscriptsBurned Context triple: [Disputation of Paris, numberOfManuscriptsBurned, thousands of Hebrew manuscripts]
-
A.
numberOfManuscriptsApprox
chosen
Indicates an approximate count of manuscripts associated with an entity.
-
B.
copiedManuscriptsOf
Indicates that one entity has produced or created handwritten reproductions of the manuscripts belonging to another entity.
-
C.
areManuscriptsOf
Indicates that the subject entities are manuscripts that are versions, copies, or instances of the work represented by the object entity.
-
D.
bookBurningTool
Indicates that an entity is used as a tool or instrument for burning books.
-
E.
writtenInSameManuscriptAs
Indicates that two written works or textual items appear together within the same physical or digital manuscript.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778b8b648190b80badaf15be2599 |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e5762655ac8190a8cc48a29fa2c0c4 |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:20 a.m.