Triple
T6771189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fon language |
E155044
|
entity |
| Predicate | hasATRVowelHarmony |
P15727
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Fon language, hasATRVowelHarmony, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasATRVowelHarmony Context triple: [Fon language, hasATRVowelHarmony, false]
-
A.
hasVowelHarmony
chosen
Indicates that the phonological vowels in a word or morpheme conform to a systematic harmony pattern (e.g., all front or all back vowels) according to the language’s vowel harmony rules.
-
B.
hasConsonantHarmony
Indicates that the entities are related by a pattern where consonants within a linguistic unit adjust to share similar features, creating consonant harmony.
-
C.
hasVowelSystem
Indicates that an entity possesses a particular system or pattern of vowel sounds (a structured set of vowel phonemes or contrasts).
-
D.
hasNasalVowels
Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
-
E.
hasVowelFeature
Indicates that an entity possesses a specific vowel-related phonological or articulatory feature.
- 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_69c68812ef7c819099369f51febb725c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2496fa08190895d8b625fb0d699 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d094105881909c5806eb4afa6306 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.