Triple
T19561033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clarence Island ice cap |
E489449
|
entity |
| Predicate | hasMassType |
P1845
|
FINISHED |
| Object | ice mass |
—
|
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: ice mass | Statement: [Clarence Island ice cap, hasMassType, ice mass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMassType Context triple: [Clarence Island ice cap, hasMassType, ice mass]
-
A.
hasMassBaseAmong
Indicates that one entity possesses a fundamental or baseline mass value when considered among a specified group or context.
-
B.
hasMassScale
Indicates that an entity is associated with a particular mass measurement scale or system used to quantify its mass.
-
C.
hasMasses
Indicates that one entity possesses or is associated with one or more masses (quantities of matter).
-
D.
hasMassTerm
Indicates that one entity is classified as a mass (uncountable) term associated with another entity.
-
E.
hasMaterialType
chosen
Indicates that something is composed of, made from, or characterized by a specific type of material.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f7442e08190ad030151ec0a97d4 |
completed | April 20, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69e514d4df3c8190b7e9b3b4fdf9452a |
completed | April 19, 2026, 5:45 p.m. |
Created at: April 10, 2026, 1:42 p.m.