Triple
T14485753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBDA Spain |
E359224
|
entity |
| Predicate | isPartOfIndustrialGroup |
P114407
|
FINISHED |
| Object | Airbus-related industrial network |
—
|
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: Airbus-related industrial network | Statement: [MBDA Spain, isPartOfIndustrialGroup, Airbus-related industrial network]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfIndustrialGroup Context triple: [MBDA Spain, isPartOfIndustrialGroup, Airbus-related industrial network]
-
A.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
-
B.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
-
C.
isIndustrialCommunity
Indicates that a community is primarily characterized by industrial activities, such as manufacturing, production, or related industrial operations.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924ee0f08190baf68318b41fa64d |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:20 a.m.