Triple
T28720336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakhdar Boumediene |
E730075
|
entity |
| Predicate | occupationBeforeDetention |
P107616
|
FINISHED |
| Object | humanitarian aid worker |
—
|
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: humanitarian aid worker | Statement: [Lakhdar Boumediene, occupationBeforeDetention, humanitarian aid worker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationBeforeDetention Context triple: [Lakhdar Boumediene, occupationBeforeDetention, humanitarian aid worker]
-
A.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
C.
occupationDuty
Indicates that an occupation entails a specific duty, responsibility, or task that is expected to be performed as part of that role.
-
D.
resumedOccupation
Indicates that an entity has returned to and continued a previous occupation or role after a period of interruption or absence.
-
E.
originalHolderOccupation
Indicates the occupation or professional role held by the entity that originally possessed or owned 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_69f043e91fe48190b73bcd8e08d433e0 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 5:53 a.m.