Triple
T6701035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proto-Bantu |
E152878
|
entity |
| Predicate | hasReconstructionGoal |
P58478
|
FINISHED |
| Object | phonology |
—
|
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: phonology | Statement: [Proto-Bantu, hasReconstructionGoal, phonology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReconstructionGoal Context triple: [Proto-Bantu, hasReconstructionGoal, phonology]
-
A.
hasReconstructionPurpose
chosen
Indicates that something exists or is performed with the specific aim or function of reconstruction (e.g., rebuilding, restoring, or re-creating something).
-
B.
hasReconstructionStandard
Indicates that something is associated with or governed by a specific standard or guideline for how it should be reconstructed.
-
C.
hasReconstructionLevel
Indicates the degree or stage to which something has been rebuilt, restored, or reconstructed.
-
D.
hasReconstructionType
Indicates the specific method or category of reconstruction applied to an object, structure, or dataset.
-
E.
containsReconstructionOf
Indicates that one entity includes or incorporates a recreated, restored, or reconstructed version of another entity.
- 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_69c68807adbc8190b8632df42b39eda0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:05 p.m.