Triple
T5845983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 2 (Lisbon Humberto Delgado Airport) |
E129710
|
entity |
| Predicate | hasRegulationType |
P14058
|
FINISHED |
| Object | commercial aviation |
—
|
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: commercial aviation | Statement: [Terminal 2 (Lisbon Humberto Delgado Airport), hasRegulationType, commercial aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegulationType Context triple: [Terminal 2 (Lisbon Humberto Delgado Airport), hasRegulationType, commercial aviation]
-
A.
regulatoryType
chosen
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
-
B.
hasRegulations
Indicates that one entity imposes, contains, or is associated with rules or regulatory requirements that govern the behavior or operation of another entity.
-
C.
worksOnRegulationType
Indicates that an entity is involved in work or activities related to a specific type or category of regulation.
-
D.
subjectToRegulation
Indicates that an entity is governed, constrained, or controlled by a specific rule, law, or regulatory framework.
-
E.
supportsRegulation
Indicates that one entity endorses, backs, or advocates for the implementation or continuation of a specific regulation.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.