Triple
T35429887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MMCM |
E1024026
|
entity |
| Predicate | appliesToAirportUse |
P199548
|
FINISHED |
| Object | civil 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: civil aviation | Statement: [MMCM, appliesToAirportUse, civil aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToAirportUse Context triple: [MMCM, appliesToAirportUse, civil aviation]
-
A.
appliesToAirport
Indicates that something is relevant, valid, or specifically intended for use at a particular airport.
-
B.
appliesToAirportName
Indicates that something is relevant or specifically associated with the name of an airport.
-
C.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
D.
designedForAirports
Indicates that something is specifically created or optimized to be used in or meet the needs of airports.
-
E.
hasAirportRelatedFunction
Indicates that something performs a role, service, or activity specifically related to the operation, support, or functioning of an airport.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
| PDg | Predicate description generation | batch_69ff4163a8548190b0eaafd0a377b141 |
completed | May 9, 2026, 2:14 p.m. |
Created at: May 3, 2026, 4:03 p.m.