Triple
T35530178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woleai script |
E1026776
|
entity |
| Predicate | hasLogographicComponent |
P181739
|
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: [Woleai script, hasLogographicComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLogographicComponent Context triple: [Woleai script, hasLogographicComponent, yes]
-
A.
hasLogographicSign
chosen
Indicates that an entity is associated with or represented by a logographic sign (a written symbol that stands for a word or morpheme).
-
B.
usesLogogramsFrom
Indicates that one writing system or notation incorporates or employs logographic characters originating from another system.
-
C.
hasPhonographicComponent
Indicates that one entity includes, contains, or is associated with a phonographic (sound-recording) component as part of its composition or structure.
-
D.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
-
E.
haveWritingSystemsForSomeMembers
Indicates that at least some members of a group or category possess or use one or more writing systems.
- 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff2636e2bc8190bba91eff91431c6e |
completed | May 9, 2026, 12:19 p.m. |
| PD | Predicate disambiguation | batch_69ff25c65be48190868480d94e1c4e89 |
completed | May 9, 2026, 12:17 p.m. |
Created at: May 3, 2026, 4:04 p.m.