Triple
T169522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aquarium Kaiyukan |
E3087
|
entity |
| Predicate | numberOfTanks |
P5289
|
FINISHED |
| Object | over 10 main tanks |
—
|
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: over 10 main tanks | Statement: [Aquarium Kaiyukan, numberOfTanks, over 10 main tanks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTanks Context triple: [Aquarium Kaiyukan, numberOfTanks, over 10 main tanks]
-
A.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
-
B.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
C.
numberOfRivets
Indicates the quantitative relationship specifying how many rivets are associated with a given object or structure.
-
D.
numberOfEngines
Indicates the quantity of engines associated with or used by an entity.
-
E.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
- F. None of above. chosen
Provenance (4 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b6f4f88190b1264bbbeb19a29e |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25665f5b8819096ca3e084faf976e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25710bdfc81909b6697159104cf53 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:34 a.m.