Triple
T1640327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Seventh Fleet |
E35453
|
entity |
| Predicate | typicalPersonnelStrength |
P24266
|
FINISHED |
| Object | 50000 sailors and Marines (approximate) |
—
|
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: 50000 sailors and Marines (approximate) | Statement: [United States Seventh Fleet, typicalPersonnelStrength, 50000 sailors and Marines (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalPersonnelStrength Context triple: [United States Seventh Fleet, typicalPersonnelStrength, 50000 sailors and Marines (approximate)]
-
A.
personnelStrength
chosen
Indicates the number or capacity of people assigned to or available for a particular unit, organization, or operation.
-
B.
typicalMembers
Indicates that the related entities are representative or characteristic members of a larger group, category, or class.
-
C.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
D.
personnelComposition
Indicates the makeup or distribution of people or roles within a group, organization, or unit.
-
E.
personnelType
Indicates the classification or role category assigned to a person within an organization or system.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.