Triple
T3852303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neutral Buoyancy Laboratory |
E85323
|
entity |
| Predicate | hasApproximatePoolVolume |
P13057
|
FINISHED |
| Object | about 23.5 million liters |
—
|
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 23.5 million liters | Statement: [Neutral Buoyancy Laboratory, hasApproximatePoolVolume, about 23.5 million liters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximatePoolVolume Context triple: [Neutral Buoyancy Laboratory, hasApproximatePoolVolume, about 23.5 million liters]
-
A.
waterVolume
chosen
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
B.
isReservoirOn
Indicates that a reservoir is physically located on or situated atop another specified entity or structure.
-
C.
hasPoolBar
Indicates that a place or facility includes a bar located in or directly adjacent to a swimming pool.
-
D.
hasPoolLength
Indicates that an entity (such as a pool) has a specific measured length.
-
E.
numberOfPools
Indicates the total count of pools associated with or contained by a given entity.
- 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.