Triple
T37490955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean-Pierre Bemba |
E931684
|
entity |
| Predicate | ICCCaseNumber |
P76198
|
FINISHED |
| Object | ICC-01/05-01/08 |
—
|
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: ICC-01/05-01/08 | Statement: [Jean-Pierre Bemba, ICCCaseNumber, ICC-01/05-01/08]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ICCCaseNumber Context triple: [Jean-Pierre Bemba, ICCCaseNumber, ICC-01/05-01/08]
-
A.
ICJCaseName
Indicates that a particular legal case is identified by a specific official name as recognized by the International Court of Justice (ICJ).
-
B.
tribunalNumber
Indicates the identifying number assigned to a specific tribunal within a legal or administrative system.
-
C.
courtNumber
Indicates the specific numbered court (e.g., field, room, or venue) assigned or associated with an event, case, or match.
-
D.
caseNumber
chosen
Indicates the unique identifying number assigned to a particular legal or administrative case.
-
E.
judicialCircuitNumber
Indicates the specific numbered judicial circuit with which an entity (such as a court or case) is associated.
- 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_69f76ec457a4819094eeb3aed9baac11 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fba68077788190b311e027435fcf87 |
completed | May 6, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fba34c65ac8190b298f0f00d1dcc0e |
completed | May 6, 2026, 8:23 p.m. |
Created at: May 3, 2026, 4:17 p.m.