Triple
T29201562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logba people |
E740287
|
entity |
| Predicate | hasExonymLanguageName |
P4705
|
FINISHED |
| Object | Logba |
—
|
NE NERFINISHED |
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: Logba | Statement: [Logba people, hasExonymLanguageName, Logba]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExonymLanguageName Context triple: [Logba people, hasExonymLanguageName, Logba]
-
A.
hasExonym
chosen
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
B.
hasDemonymLanguage
Indicates that a language is used as the demonym (people’s name or adjective of nationality) for inhabitants of a particular place or group.
-
C.
hasEndonymLanguage
Indicates that the language specified is the one in which a name or term is expressed in its own native or local form.
-
D.
exonymStatus
Indicates the status or classification of a name used in one language to refer to a place, people, or entity known by a different name in its own language.
-
E.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: April 28, 2026, 12:06 p.m.