Triple
T19467446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles-class submarine |
E487035
|
entity |
| Predicate | totalUnitsCompleted |
P19248
|
FINISHED |
| Object | 62 |
—
|
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: 62 | Statement: [Los Angeles-class submarine, totalUnitsCompleted, 62]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalUnitsCompleted Context triple: [Los Angeles-class submarine, totalUnitsCompleted, 62]
-
A.
completedIn
Indicates that an action, process, or task was fully finished within a specified time period or duration.
-
B.
numberOfUnits
chosen
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
C.
numberOfCompletedParts
Indicates the count of parts within a whole that have been finished or fully completed.
-
D.
completionRate
Indicates the proportion of a task, process, or set of items that has been finished relative to its total intended amount.
-
E.
numberOfRulesCompleted
Indicates the count of rules that have been successfully completed or satisfied in a given context.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e2aee081908330a5665fa60482 |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.