Triple
T24798993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malakula languages |
E620467
|
entity |
| Predicate | belongToMacroArea |
P80001
|
FINISHED |
| Object | Papunesia |
—
|
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: Papunesia | Statement: [Malakula languages, belongToMacroArea, Papunesia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongToMacroArea Context triple: [Malakula languages, belongToMacroArea, Papunesia]
-
A.
hasMacroArea
chosen
Indicates that one entity belongs to, or is located within, a broader geographic or conceptual macro-area represented by another entity.
-
B.
belongsToEconomicMacroregion
Indicates that one economic region or area is part of, or classified within, a larger economic macroregion.
-
C.
hasEthnologueMacroArea
Indicates that something belongs to, or is classified within, a specific macro-geographical area as defined by Ethnologue.
-
D.
isOneOfMainAreasFor
Indicates that something belongs to the primary set of domains, topics, or fields associated with another entity.
-
E.
isPartOfBusinessArea
Indicates that one entity belongs to, is included within, or falls under the scope of a particular business area.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 4:49 a.m.