Triple
T22685101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ala Ndigbo |
E560888
|
entity |
| Predicate | tabooType |
P60363
|
FINISHED |
| Object | abominations against the land |
—
|
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: abominations against the land | Statement: [Ala Ndigbo, tabooType, abominations against the land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tabooType Context triple: [Ala Ndigbo, tabooType, abominations against the land]
-
A.
tabooInTradition
chosen
Indicates that performing or engaging in the referenced action or relationship is considered forbidden or strongly disapproved of within a particular cultural or religious tradition.
-
B.
tabooPeriod
Indicates a time span during which a particular action, interaction, or relationship is socially or ritually prohibited.
-
C.
hasBuildingMaterialTaboo
Indicates that a subject is prohibited or culturally restricted from using a particular material in the construction of buildings.
-
D.
typeOfCensure
Indicates the specific kind or category of censure applied in a given disciplinary or critical action.
-
E.
prohibits
Indicates that one entity forbids or disallows another entity from performing a specific action or being in a certain state.
- 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_69e2454d71b48190a1f80af9f82b6fcf |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17862c8a48190912a8ad09dfda795 |
completed | April 29, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69ee62b2259c819091ed1387a748b9f3 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:12 p.m.