Triple
T23846329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mac. Robertson Land |
E592030
|
entity |
| Predicate | coastCharacter |
P80209
|
FINISHED |
| Object | heavily glaciated coast |
—
|
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: heavily glaciated coast | Statement: [Mac. Robertson Land, coastCharacter, heavily glaciated coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coastCharacter Context triple: [Mac. Robertson Land, coastCharacter, heavily glaciated coast]
-
A.
exteriorCharacter
chosen
Indicates a relationship where one entity’s outward or visible qualities, features, or appearance are being characterized or described.
-
B.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
C.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
metCharacter
Indicates that one entity has encountered or been introduced to another entity at least once.
- 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_69e25d221d908190b9b502ad31e66a3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c88c9bbc81909204120279e6d980 |
completed | April 29, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f1614612b481908c45d99e588882f9 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:10 p.m.