Triple
T15651649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ikwerre Igbo |
E376325
|
entity |
| Predicate | hasEndangermentFactors |
P106049
|
FINISHED |
| Object | urbanization |
—
|
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: urbanization | Statement: [Ikwerre Igbo, hasEndangermentFactors, urbanization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndangermentFactors Context triple: [Ikwerre Igbo, hasEndangermentFactors, urbanization]
-
A.
isEndangeredDueTo
chosen
Indicates that an entity is endangered as a result of the specific cause or factor represented by the related entity.
-
B.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
C.
endangerment
Indicates a relationship in which one entity exposes another to potential harm, risk, or danger.
-
D.
hasConservationConcernIn
Indicates that an entity is subject to a specified conservation concern status within a particular geographic area or jurisdiction.
-
E.
hasEnvironmentalRisk
Indicates that an entity poses, contributes to, or is associated with potential harm or adverse impact on the environment.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eeed2d48190a7a8a618d90012d0 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.