Triple
T9517803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Sverdrup’s Second Fram Expedition 1898–1902 |
E229568
|
entity |
| Predicate | expandedKnowledgeOf |
P81810
|
FINISHED |
| Object | Arctic geography |
—
|
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: Arctic geography | Statement: [Otto Sverdrup’s Second Fram Expedition 1898–1902, expandedKnowledgeOf, Arctic geography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: expandedKnowledgeOf Context triple: [Otto Sverdrup’s Second Fram Expedition 1898–1902, expandedKnowledgeOf, Arctic geography]
-
A.
knows
Indicates that one entity has knowledge or awareness of another entity or piece of information.
-
B.
usesKnowledgeOf
Indicates that one entity applies or draws upon the knowledge possessed by another entity in performing an action or achieving a result.
-
C.
expandedBy
Indicates that one entity increases, elaborates, or builds upon the scope, detail, or extent of another entity.
-
D.
expandedAs
Indicates that one entity is a more detailed, elaborated, or fully written-out form of another, capturing how the latter is expanded from the former.
-
E.
knowledgeOutput
chosen
Indicates that an entity produces, expresses, or makes available knowledge, information, or learned content as an output.
- 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_69ca84777560819084cddd999badc1aa |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9880417c819097dde277988df36d |
completed | April 1, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cca56a3d088190bdc16670678fb6c6 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:59 p.m.