Triple
T6464321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Ugly Fat Fellow |
E142194
|
entity |
| Predicate | appliesToAircraftConfiguration |
P3541
|
FINISHED |
| Object | eight-engine bomber |
—
|
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: eight-engine bomber | Statement: [Big Ugly Fat Fellow, appliesToAircraftConfiguration, eight-engine bomber]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToAircraftConfiguration Context triple: [Big Ugly Fat Fellow, appliesToAircraftConfiguration, eight-engine bomber]
-
A.
aircraftConfiguration
chosen
Indicates the specific arrangement or setup of an aircraft’s components, systems, or features for a given purpose or operating condition.
-
B.
aircraftConfigurationProduced
Indicates that a specific aircraft configuration has been manufactured or produced.
-
C.
supportsAircraft
Indicates that one entity is capable of accommodating, carrying, or enabling the operation of an aircraft.
-
D.
usedOnAircraftName
Indicates that something is employed or applied on an aircraft identified by a specific name.
-
E.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
- 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a10305081909521ee200cf70a30 |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:49 p.m.