Triple
T13160497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sena of Tete |
E312712
|
entity |
| Predicate | hasLanguageCodeParent |
P13919
|
FINISHED |
| Object | sna (Sena) |
—
|
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: sna (Sena) | Statement: [Sena of Tete, hasLanguageCodeParent, sna (Sena)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageCodeParent Context triple: [Sena of Tete, hasLanguageCodeParent, sna (Sena)]
-
A.
hasSuperordinateLanguage
Indicates that one language serves as a higher-level, overarching, or more general language in relation to another language.
-
B.
hasPrimaryLanguageSubbranch
Indicates that one language subbranch is the main or principal subbranch associated with a given language or language family.
-
C.
hasSecondaryLanguageFamily
Indicates that an entity has an additional, non-primary association with a particular language family.
-
D.
hasLinguisticCode
chosen
Indicates that an entity is associated with a specific linguistic identifier or code (such as a language or script code) that characterizes its linguistic properties.
-
E.
hasSubLanguage
Indicates that one language is a subset, variant, or specialized form of another language.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:12 p.m.