Triple
T10288165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martta |
E241287
|
entity |
| Predicate | hasTwoConsonantsEmphasized |
P84187
|
FINISHED |
| Object | tt |
—
|
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: tt | Statement: [Martta, hasTwoConsonantsEmphasized, tt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwoConsonantsEmphasized Context triple: [Martta, hasTwoConsonantsEmphasized, tt]
-
A.
hasConsonantHarmony
Indicates that the entities are related by a pattern where consonants within a linguistic unit adjust to share similar features, creating consonant harmony.
-
B.
usesConsonantInitials
Indicates that an entity’s initials or abbreviated form begin with consonant letters rather than vowels.
-
C.
hasGeminateConsonants
chosen
Indicates that a word, morpheme, or phonological form contains one or more geminate (doubled or lengthened) consonant sounds.
-
D.
hasConsonantPhonemes
Indicates that an entity possesses or includes one or more consonant phonemes in its phonological system.
-
E.
hasConsonantLengthContrast
Indicates that a language distinguishes meaning between words based on differences in the length or duration of consonant sounds.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:41 a.m.