Triple
T13986542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Challenger expedition |
E336454
|
entity |
| Predicate | reportVolumes |
P2734
|
FINISHED |
| Object | 50 |
—
|
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: 50 | Statement: [Challenger expedition, reportVolumes, 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reportVolumes Context triple: [Challenger expedition, reportVolumes, 50]
-
A.
numberOfVolumes
chosen
Indicates the total count of separate volumes or parts that make up a multi-volume work or collection.
-
B.
volumeOf
Indicates the quantitative three-dimensional space occupied by an entity or contained within an object.
-
C.
reporterNameVolumeRange
Indicates that a reporter’s name is associated with a specific range of volume numbers in which they appear or are relevant.
-
D.
volumeInUnitedStatesReports
Indicates that a legal case or decision is published in a specified volume of the United States Reports.
-
E.
collectionVolume
Indicates the total physical or spatial amount occupied by a collection, such as its size, capacity, or volume.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2ea3e5a081908ed8ead108139252 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
Created at: April 9, 2026, 10:18 p.m.