Triple
T9414371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudy Law |
E226977
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Law |
E549738
|
NE 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: Law | Statement: [Rudy Law, familyName, Law]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Law Context triple: [Rudy Law, familyName, Law]
-
A.
Law
Law is the system of rules and principles recognized by a community or government as regulating the actions of its members and enforceable by legal institutions.
-
B.
Law
chosen
Law is a common English-language surname borne by various notable individuals, including political figures such as former British Prime Minister Andrew Bonar Law.
-
C.
Law family
The Law family is a British show-business family best known for including actor Jude Law and his model daughter Iris Law.
-
D.
Law and Justice
Law and Justice is a right-wing populist and national-conservative political party in Poland that has been one of the country’s dominant governing forces in the 21st century.
-
E.
Laws
Laws is one of Plato’s late philosophical dialogues, presenting a detailed exploration of legal theory, political organization, and the ideal constitution for a well-ordered city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68c7bd648190b17f082883c98239 |
completed | April 1, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d107b63cf48190a072e3434a7b85a8 |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:47 p.m.