Triple
T3298873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geʽez script |
E69281
|
entity |
| Predicate | hasPunctuationSystem |
P47834
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Geʽez script, hasPunctuationSystem, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPunctuationSystem Context triple: [Geʽez script, hasPunctuationSystem, true]
-
A.
usesPhoneticSystem
Indicates that one entity employs or is based on a particular phonetic system for representing or encoding sounds.
-
B.
hasSyllabary
Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
-
C.
hasPronounSystem
Indicates that an entity possesses or employs a particular system or set of rules for using pronouns.
-
D.
hasSyllabicStructure
Indicates that an entity possesses a specific arrangement or pattern of syllables, such as their number, order, or type.
-
E.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0a49b748190b6db99a85c3cb3c5 |
completed | March 8, 2026, 5:23 p.m. |
| PD | Predicate disambiguation | batch_69ada42407dc81909f60d7a14e1b7934 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada526764881908e4bd52938d5374d |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:11 p.m.