Triple
T38092385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BEAM |
E951147
|
entity |
| Predicate | diameterExpanded |
P7302
|
FINISHED |
| Object | about 3.2 meters |
—
|
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 3.2 meters | Statement: [BEAM, diameterExpanded, about 3.2 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diameterExpanded Context triple: [BEAM, diameterExpanded, about 3.2 meters]
-
A.
approximateDiameter
chosen
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
B.
bodyDiameter
Indicates the measurement of how wide an object's body is across its broadest cross-section.
-
C.
diameterMini
Indicates that one entity is the minimum diameter measurement associated with another entity.
-
D.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
E.
correctorPlateDiameter
Indicates the relationship where a corrector plate is associated with a specific measurement of its diameter.
- 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_69f76f04960c8190a83f14ae4c67f5bc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc4748843c8190931432653be4890c |
completed | May 7, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69fc45646ce481908caf292ff9f06e15 |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 3, 2026, 4:21 p.m.