Triple
T16307571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LCK |
E395960
|
entity |
| Predicate | airportFocus |
P16381
|
FINISHED |
| Object | cargo operations |
—
|
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: cargo operations | Statement: [LCK, airportFocus, cargo operations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airportFocus Context triple: [LCK, airportFocus, cargo operations]
-
A.
airportUse
Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
-
B.
associatedAirportFocusCityFor
Indicates that an airport serves as a designated focus city for a particular airline or carrier.
-
C.
airportCodeContext
Indicates that an airport code is being used or interpreted within a specific contextual framework (such as a region, system, or standard) that defines its meaning.
-
D.
hubAirport
Indicates that an airport serves as a primary hub or central operating base for a particular airline or carrier.
-
E.
airportServesAs
chosen
Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d63b688190ad5ebc3fb5dd5b4c |
completed | April 17, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.