Triple
T32754849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geʽez language |
E837593
|
entity |
| Predicate | hasAncientLiterature |
P86096
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Geʽez language, hasAncientLiterature, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAncientLiterature Context triple: [Geʽez language, hasAncientLiterature, yes]
-
A.
hasAncientLiteraryTradition
chosen
Indicates that an entity possesses a long-established, historically significant body of written literature originating in ancient times.
-
B.
hasClassicalLiterature
Indicates that an entity is associated with, contains, or possesses works of classical literature.
-
C.
hasWritingTraditionSince
Indicates that a writing tradition has been present or established for an entity starting from a specified point in time.
-
D.
hasWritingTraditionVia
Indicates that an entity possesses or participates in a writing tradition by means of, or through the mediation of, another specified entity or method.
-
E.
hasEarliestKnownLiteraryVersion
Indicates that one entity is the earliest known literary version or attested written form of another entity (such as a story, motif, or tradition).
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 1, 2026, 1:12 a.m.