Triple
T3839722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1036 Ganymed |
E93420
|
entity |
| Predicate | largestInClass |
P4495
|
FINISHED |
| Object | near-Earth objects |
—
|
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: near-Earth objects | Statement: [1036 Ganymed, largestInClass, near-Earth objects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestInClass Context triple: [1036 Ganymed, largestInClass, near-Earth objects]
-
A.
isLargestOf
chosen
Indicates that one entity has the greatest size, extent, or magnitude among a specified set of entities.
-
B.
numberInClass
Indicates that a specified entity is a member of, or belongs to, a particular class or category.
-
C.
heightClass
Indicates the categorical height level or range to which an entity is assigned (e.g., short, medium, tall).
-
D.
areLargestGroupIn
Indicates that one group is the biggest or most numerous among all groups within a specified context or set.
-
E.
highestRankIn
Indicates that one entity holds the top or most senior rank within a specified group, category, or context relative to other entities.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeeba1535c8190b36e2ab2d4514b54 |
completed | March 9, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.