Triple
T27684991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | people's courts of the People's Republic of China |
E698001
|
entity |
| Predicate | hasSeatOfTopCourtIn |
P141442
|
FINISHED |
| Object | Beijing |
—
|
NE NERFINISHED |
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: Beijing | Statement: [people's courts of the People's Republic of China, hasSeatOfTopCourtIn, Beijing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatOfTopCourtIn Context triple: [people's courts of the People's Republic of China, hasSeatOfTopCourtIn, Beijing]
-
A.
capitalCityOfCourt
chosen
Indicates that a city serves as the official seat or capital location of a particular court.
-
B.
hadRulingSeat
Indicates that an entity held an official position of authority or judgment within a governing or decision-making body.
-
C.
highCourtSeat
Indicates that a location serves as the official seat or headquarters of a high court.
-
D.
hasJudicialHeadquarters
Indicates that a judicial body or system is officially based or headquartered at a specific location.
-
E.
highestCourtOf
Indicates that one entity is the supreme judicial authority or top-level court within the jurisdiction or legal system of another entity.
- 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_69ef590df8708190af5488f0638e790c |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69fcef654d588190b29ecc76678d1aa0 |
completed | May 7, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69fcecdb97f48190b382b7d13be92dc0 |
completed | May 7, 2026, 7:49 p.m. |
Created at: April 27, 2026, 2:49 p.m.