Triple
T17762089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neumayer Station III |
E443401
|
entity |
| Predicate | maximumPersonnel |
P24266
|
FINISHED |
| Object | around 40 in summer |
—
|
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: around 40 in summer | Statement: [Neumayer Station III, maximumPersonnel, around 40 in summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumPersonnel Context triple: [Neumayer Station III, maximumPersonnel, around 40 in summer]
-
A.
maximumAuthorizedPersonnel
Indicates the highest number of personnel that are permitted or authorized for a given role, location, or context.
-
B.
maximumAuthorizedPolicePersonnel
Indicates the highest number of police personnel that are officially permitted or authorized for a given jurisdiction, unit, or context.
-
C.
personnelStrength
chosen
Indicates the number or capacity of people assigned to or available for a particular unit, organization, or operation.
-
D.
soldiersCapacity
Indicates the maximum number of soldiers that an entity can hold, support, or accommodate.
-
E.
restrictedArmySizeOf
Indicates that one entity imposes a limitation or cap on the allowable size of another entity’s army.
- 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e485f887ac81908c896a50175692b9 |
completed | April 19, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:11 a.m.