Triple
T8930673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | judiciary of Ceylon |
E212644
|
entity |
| Predicate | hadProfessionalRole |
P4325
|
FINISHED |
| Object | judges of Ceylon |
—
|
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: judges of Ceylon | Statement: [judiciary of Ceylon, hadProfessionalRole, judges of Ceylon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadProfessionalRole Context triple: [judiciary of Ceylon, hadProfessionalRole, judges of Ceylon]
-
A.
workedAs
chosen
Indicates that an entity held a particular job, role, or position, performing work in that capacity.
-
B.
hasProductionRole
Indicates that an entity holds a specific role or function in the production or creation process of another entity.
-
C.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
-
D.
hasOccupationDuringStory
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
-
E.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
- 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_69ca8395c438819087d7cb844ab5990c |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6676d5d881908ce78cbb5561a68b |
completed | April 1, 2026, 12:27 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed3286c8190a21de2ee11f2639f |
completed | March 31, 2026, 11:54 p.m. |
Created at: March 30, 2026, 6:57 p.m.