Triple
T3581557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hawker Siddeley Trident |
E75809
|
entity |
| Predicate | airlineMarket |
P49863
|
FINISHED |
| Object | short-haul European routes |
—
|
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: short-haul European routes | Statement: [Hawker Siddeley Trident, airlineMarket, short-haul European routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineMarket Context triple: [Hawker Siddeley Trident, airlineMarket, short-haul European routes]
-
A.
airline
Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
-
B.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
C.
airlineScale
Indicates that one airline is a subsidiary, regional brand, or otherwise operates at a smaller or supporting scale relative to another airline.
-
D.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
E.
hasAirlines
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc102cb2881908fa4dc1bf6fa5961 |
completed | March 8, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69adb83810c481909c645c08b978edc1 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb8e4ba948190a9b777cf7f788b96 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:21 p.m.