Triple
T15800312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abdelbaset al-Megrahi |
E383079
|
entity |
| Predicate | minimumTerm |
P120117
|
FINISHED |
| Object | 27 years |
—
|
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: 27 years | Statement: [Abdelbaset al-Megrahi, minimumTerm, 27 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumTerm Context triple: [Abdelbaset al-Megrahi, minimumTerm, 27 years]
-
A.
minimumGrant
Indicates that there is a lowest allowable or required amount of a grant associated with an entity or agreement.
-
B.
minimumLevel
Indicates that one entity specifies the lowest allowable or required level, degree, or threshold at which another entity, condition, or action becomes valid or applicable.
-
C.
minimumMass
Indicates the smallest mass value that an entity or system is required, allowed, or observed to have within a given context.
-
D.
maximumTermCount
Indicates the highest number of terms that are allowed or considered within a given context or operation.
-
E.
minimumSize
Indicates that there is a lower bound or smallest allowable value for the size of something in the relationship.
- F. None of above. chosen
Provenance (4 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4e135b08190b736e77bac5e2bff |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0053b847c8190945726c3ddac21cc |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e00e48d49c819081afccb02f9cf18b |
completed | April 15, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:48 a.m.