Triple
T30240297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santos-Dumont No. 5 |
E768892
|
entity |
| Predicate | hasEngineLocation |
P183123
|
FINISHED |
| Object | mounted on the gondola |
—
|
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: mounted on the gondola | Statement: [Santos-Dumont No. 5, hasEngineLocation, mounted on the gondola]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEngineLocation Context triple: [Santos-Dumont No. 5, hasEngineLocation, mounted on the gondola]
-
A.
hasEngineProgram
Indicates that an entity is associated with or participates in a specific engine-related program.
-
B.
hasEngineTypeOnDisplay
Indicates that a particular type of engine is being shown or presented as part of a display or exhibition.
-
C.
mainEnginesInstalled
Indicates that the primary engines have been fitted and secured onto the relevant system or structure.
-
D.
hasCrankshaftPosition
Indicates that an entity has or is associated with a specific crankshaft position in a mechanical or engine context.
-
E.
originatesFromEngine
Indicates that something has its source, cause, or production in a particular engine.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f798387ea481909f51303f53a22e52 |
completed | May 3, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79798663481908d6bc48dd6a94ca6 |
completed | May 3, 2026, 6:44 p.m. |
Created at: April 29, 2026, 7:38 p.m.