Triple
T31006174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malalai Joya |
E790070
|
entity |
| Predicate | hasReceivedThreatsFrom |
P73999
|
FINISHED |
| Object | Taliban |
—
|
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: Taliban | Statement: [Malalai Joya, hasReceivedThreatsFrom, Taliban]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReceivedThreatsFrom Context triple: [Malalai Joya, hasReceivedThreatsFrom, Taliban]
-
A.
hasThreats
chosen
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
B.
hasThreatType
Indicates that an entity is associated with, or characterized by, a specific type or category of threat.
-
C.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
-
D.
isThreatenedCategory
Indicates that an entity belongs to a category facing risk of harm, decline, or extinction.
-
E.
threatsFaced
Indicates that an entity is exposed to or experiences specific dangers, risks, or harmful conditions.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00c3362dcc819096e49b882709fddd |
completed | May 10, 2026, 5:41 p.m. |
| PD | Predicate disambiguation | batch_6a00c2e5cdd88190a5f2d0f6a843cd56 |
completed | May 10, 2026, 5:39 p.m. |
Created at: April 29, 2026, 8:57 p.m.