Triple
T1493112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osphranter rufus |
E29625
|
entity |
| Predicate | largestLiving |
P28614
|
FINISHED |
| Object | marsupial |
—
|
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: marsupial | Statement: [Osphranter rufus, largestLiving, marsupial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestLiving Context triple: [Osphranter rufus, largestLiving, marsupial]
-
A.
largestInCountry
Indicates that an entity is the largest of its kind within the specified country.
-
B.
hasLivingSpecies
Indicates that an entity currently contains, supports, or is associated with one or more species that are alive or extant.
-
C.
largestNationalPark
Indicates that the subject is the largest national park within the specified country or region.
-
D.
hasLargestContinuousLandAreaOn
Indicates that an entity possesses the greatest uninterrupted expanse of land on a specified geographic region or surface compared to all other entities.
-
E.
notableSpecies
Indicates that the subject is known for, or significantly associated with, the specified species.
- F. None of above. chosen
Provenance (4 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c665488190ae665f7a1b0563f5 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c52c703c8190a56389b09d97659f |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8:12 p.m.