Triple
T14692529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libya situation at the ICC |
E345069
|
entity |
| Predicate | referralResolutionNumber |
P26175
|
FINISHED |
| Object | 1970 |
—
|
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: 1970 | Statement: [Libya situation at the ICC, referralResolutionNumber, 1970]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referralResolutionNumber Context triple: [Libya situation at the ICC, referralResolutionNumber, 1970]
-
A.
refnum
chosen
Indicates that an entity is associated with a specific reference number used to identify or track it.
-
B.
disputeSettlementNumber
Indicates the identifying number assigned to a specific dispute settlement case or process.
-
C.
reporterNumber
Indicates the identifier or count associated with the reporter involved in a given event or relationship.
-
D.
disputeNumber
Indicates the identifier or count associated with a specific dispute within a set of disputes.
-
E.
linkedToResolution
Indicates that something is associated with, or directly connected to, a specific resolution or decision outcome.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb585d46c81908d6964130914cec4 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.