Triple
T11000197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Destiny laboratory |
E259983
|
entity |
| Predicate | hasWindowDiameter |
P90172
|
FINISHED |
| Object | about 50 centimeters |
—
|
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 centimeters | Statement: [Destiny laboratory, hasWindowDiameter, about 50 centimeters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWindowDiameter Context triple: [Destiny laboratory, hasWindowDiameter, about 50 centimeters]
-
A.
hasRoundWindowDiameter
chosen
Indicates that an entity possesses a round window whose size is specified by its diameter.
-
B.
shellDiameter
Indicates the diameter measurement of a shell, typically specifying the distance across it at its widest point.
-
C.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
D.
approximateDiameter
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
E.
mountDiameter
Indicates the size of the circular interface where one component is mounted onto another, typically measured as the diameter of the mounting point or opening.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d796d5457c819096630246fa5f7076 |
completed | April 9, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:25 p.m.