Triple
T687695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terminal 1 (LAX) |
E13319
|
entity |
| Predicate | hasTypeOfFlights |
P18239
|
FINISHED |
| Object | scheduled passenger flights |
—
|
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: scheduled passenger flights | Statement: [Terminal 1 (LAX), hasTypeOfFlights, scheduled passenger flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfFlights Context triple: [Terminal 1 (LAX), hasTypeOfFlights, scheduled passenger flights]
-
A.
hasDomesticFlights
Indicates that an airline or airport operates flights within the same country, connecting domestic destinations.
-
B.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
C.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
D.
hasInternationalFlights
Indicates that an airport or airline operates flights connecting to destinations in other countries.
-
E.
numberOfFlights
Indicates the total count of flights associated with a given entity or within a specified context.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d2048d48190ab99ab59accb6909 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a4a0f405748190ba72a9cfe946a8ec |
completed | March 1, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:36 p.m.