Triple
T7291088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kapingamarangi language |
E164392
|
entity |
| Predicate | hasWordFormation |
P75423
|
FINISHED |
| Object | reduplication |
—
|
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: reduplication | Statement: [Kapingamarangi language, hasWordFormation, reduplication]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWordFormation Context triple: [Kapingamarangi language, hasWordFormation, reduplication]
-
A.
typicalWordFormation
Indicates the usual or most common way in which a word is formed from other linguistic elements (such as roots, affixes, or compounds).
-
B.
hasPrimaryWordFormationProcess
Indicates that one entity is the main or predominant word-formation process by which another entity (typically a word or lexical item) is formed.
-
C.
hasTwoWordForm
Indicates that an entity is represented or expressed using a form consisting of exactly two words.
-
D.
compositionalForm
Indicates the structural or formal composition that defines how parts are organized or combined within something.
-
E.
hasRootWord
Indicates that one linguistic form is derived from, based on, or directly associated with a specified root word.
- 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_69c6887a499881909dd23341399c59d8 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6eb6e8f3881908628b3d41aad70c6 |
completed | March 27, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
| PDg | Predicate description generation | batch_69c6e82b0f9881909d29c99af1ea0dbf |
completed | March 27, 2026, 8:27 p.m. |
Created at: March 27, 2026, 3 p.m.