Triple
T10237742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Book II (De iure belli ac pacis) |
E243509
|
entity |
| Predicate | treatsOf |
P92913
|
FINISHED |
| Object | sources of law |
—
|
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: sources of law | Statement: [Book II (De iure belli ac pacis), treatsOf, sources of law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsOf Context triple: [Book II (De iure belli ac pacis), treatsOf, sources of law]
-
A.
treats
Indicates that one entity provides medical care or therapeutic intervention to another entity.
-
B.
يتناول
Indicates that an entity is consuming or taking something, such as food, drink, or medicine.
-
C.
hasDessert
Indicates that one entity is served, accompanied, or associated with a particular dessert item.
-
D.
servesProduct
Indicates that one entity provides or offers a particular product to others, typically in a commercial or service context.
-
E.
mayBeGivenTo
Indicates that something is permitted or eligible to be transferred, assigned, or provided from one entity to another.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d23a9c4c8190abece9e52879c479 |
completed | April 7, 2026, 9:45 a.m. |
Created at: April 6, 2026, 11:23 a.m.