Triple
T3852300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neutral Buoyancy Laboratory |
E85323
|
entity |
| Predicate | hasApproximatePoolLength |
P34006
|
FINISHED |
| Object | about 62 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 62 meters | Statement: [Neutral Buoyancy Laboratory, hasApproximatePoolLength, about 62 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximatePoolLength Context triple: [Neutral Buoyancy Laboratory, hasApproximatePoolLength, about 62 meters]
-
A.
hasPoolLength
Indicates that an entity (such as a pool) has a specific measured length.
-
B.
hasApproximateMemberCount
Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
-
C.
hasMaxLengthApprox
chosen
Indicates that something has a maximum length that is approximately equal to a specified value, allowing for some tolerance or imprecision.
-
D.
hasPool
Indicates that one entity possesses, includes, or is equipped with a swimming pool.
-
E.
hasApproximateBrickCount
Indicates that an entity is associated with an estimated or non-exact number of bricks.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec01f7b48190ba1ec89328b3fccb |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.