Triple
T15764963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F-16 program |
E382194
|
entity |
| Predicate | hasIndustrialParticipation |
P120241
|
FINISHED |
| Object | licensed production in Belgium |
—
|
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: licensed production in Belgium | Statement: [F-16 program, hasIndustrialParticipation, licensed production in Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialParticipation Context triple: [F-16 program, hasIndustrialParticipation, licensed production in Belgium]
-
A.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
B.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
-
C.
hasIndustrialDevelopment
Indicates that an entity possesses, supports, or is characterized by industrial growth, infrastructure, or manufacturing-related development.
-
D.
isPartOfIndustrialGroup
Indicates that one entity belongs to, or is a constituent member of, a larger industrial group or corporate conglomerate.
-
E.
hasIndustrialEmployer
Indicates that an entity is employed by, or has an employment relationship with, an industrial organization or company.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b8154881908afe5191e6424f15 |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e03cc871d0819085c0fc54de7984ff |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 4:47 a.m.