Triple
T135612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esperanto |
E2739
|
entity |
| Predicate | hasPhonologicalType |
P5219
|
FINISHED |
| Object | phonemic orthography |
—
|
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: phonemic orthography | Statement: [Esperanto, hasPhonologicalType, phonemic orthography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhonologicalType Context triple: [Esperanto, hasPhonologicalType, phonemic orthography]
-
A.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
-
B.
hasStressPattern
Indicates that an entity (such as a word or phrase) follows a particular arrangement of stressed and unstressed units (e.g., syllables) in its pronunciation.
-
C.
hasMorphologicalType
Indicates that an entity possesses or is classified by a particular morphological type or structural form.
-
D.
hasNumberOfConsonantLetters
Indicates the relationship between an entity and the count of consonant letters present in its written form.
-
E.
hasProtoLanguage
Indicates that a language or language family originates from, or is derived from, a specified proto-language.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a3ad908190b6a8652f09ae0cbb |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.