Triple
T15573244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morning Glory cloud |
E374299
|
entity |
| Predicate | hasTypicalWidth |
P19786
|
FINISHED |
| Object | about 1 to 2 kilometers |
—
|
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 1 to 2 kilometers | Statement: [Morning Glory cloud, hasTypicalWidth, about 1 to 2 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWidth Context triple: [Morning Glory cloud, hasTypicalWidth, about 1 to 2 kilometers]
-
A.
typicalWidth
chosen
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
B.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
C.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
D.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
E.
hasTypicalMemberSize
Indicates the usual or characteristic size associated with members of a given class or group.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e2025888190a2b6240296bba13e |
completed | April 16, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.