Triple
T59572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamorro |
E1180
|
entity |
| Predicate | hasGrammarType |
P1250
|
FINISHED |
| Object | agglutinative features |
—
|
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: agglutinative features | Statement: [Chamorro, hasGrammarType, agglutinative features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrammarType Context triple: [Chamorro, hasGrammarType, agglutinative features]
-
A.
hasSegmentType
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
B.
hasTypeName
Indicates that an entity is associated with a specific type name used to classify or identify its kind.
-
C.
hasStructureType
Indicates that an entity possesses or is classified by a specific structural type or configuration.
-
D.
hasGrammaticalGender
Indicates that one entity assigns or possesses a specific grammatical gender in relation to another entity (such as a word, phrase, or linguistic unit).
-
E.
hasMorphologicalType
chosen
Indicates that an entity possesses or is classified by a particular morphological type or structural form.
- 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_69a24a552ef88190a0df287d68c65cba |
completed | Feb. 28, 2026, 1:52 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24e9f40908190a2f4a2111469b733 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 1:55 a.m.