Triple
T30897137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khodynka Field |
E787050
|
entity |
| Predicate | airfieldStatus |
P48854
|
FINISHED |
| Object | defunct |
—
|
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: defunct | Statement: [Khodynka Field, airfieldStatus, defunct]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airfieldStatus Context triple: [Khodynka Field, airfieldStatus, defunct]
-
A.
airportStatus
chosen
Indicates the current operational condition or state of an airport (e.g., open, closed, delayed, restricted).
-
B.
aircraftStatus
Indicates the current operational condition or state of an aircraft (e.g., active, grounded, in maintenance, or decommissioned).
-
C.
airlineStatus
Indicates the current operational or membership state of an airline, such as its activity, certification, or alliance standing.
-
D.
cityTerminalStatus
Indicates the operational or functional status of a city’s terminal (such as an airport, bus, or train terminal) within a given context or system.
-
E.
flightActivity
Indicates that an entity is engaged in or associated with the operation, occurrence, or status of a flight.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:49 p.m.