Triple
T18982320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IGO |
E464458
|
entity |
| Predicate | airlineServiceModel |
P134019
|
FINISHED |
| Object | no-frills service |
—
|
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: no-frills service | Statement: [IGO, airlineServiceModel, no-frills service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineServiceModel Context triple: [IGO, airlineServiceModel, no-frills service]
-
A.
airlineService
Indicates that an airline operates transportation services (such as flights) between specified locations or for specified routes.
-
B.
airlineServiceEntry
Indicates the initiation or presence of an airline’s operational service on a particular route, schedule, or location.
-
C.
airlineContext
Indicates a relationship, situation, or action that specifically occurs within or is constrained by an airline-related context (such as flights, carriers, or air travel operations).
-
D.
airlineServiceVia
Indicates that an airline service operates between two locations with a specified intermediate stop or transit point.
-
E.
servesAirline
Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65d27548190b86d4c5f5b51d809 |
completed | April 20, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69e4a2f437648190b85650dae8885d48 |
completed | April 19, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 12:01 p.m.