Triple
T5826338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Captain Cook Memorial Jet |
E129234
|
entity |
| Predicate | nozzleDiameter |
P67408
|
FINISHED |
| Object | about 50 millimetres |
—
|
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: about 50 millimetres | Statement: [Captain Cook Memorial Jet, nozzleDiameter, about 50 millimetres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nozzleDiameter Context triple: [Captain Cook Memorial Jet, nozzleDiameter, about 50 millimetres]
-
A.
pipeDiameter
Indicates that one entity specifies or measures the diameter of a pipe associated with another entity.
-
B.
numberOfNozzles
Indicates the quantity of nozzles associated with or present on a given entity.
-
C.
nozzleExpansionRatio
Indicates the ratio between a nozzle’s exit area and its throat area, describing how much the flow expands as it passes through the nozzle.
-
D.
impactorDiameter
Indicates the size of the object that impacts another body, typically measured as the diameter of the impacting body.
-
E.
nozzleDeflectionRange
Indicates the range of angles through which a nozzle can be deflected from its neutral or reference position.
- 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_69c00849d55481908b4f9f5543e0bf6d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:53 p.m.