Triple
T9803298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidra |
E237892
|
entity |
| Predicate | hasCauseOfDisruption |
P708
|
FINISHED |
| Object | military offensives |
—
|
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: military offensives | Statement: [Sidra, hasCauseOfDisruption, military offensives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCauseOfDisruption Context triple: [Sidra, hasCauseOfDisruption, military offensives]
-
A.
disruptsContinuityOf
Indicates that one entity interrupts, breaks, or otherwise prevents the ongoing, uninterrupted progression or sequence of another entity or process.
-
B.
hasCauseOfDestruction
Indicates that one entity is the cause or agent responsible for the destruction or damage of another entity.
-
C.
hasCause
chosen
Indicates that one entity is the reason for, or brings about, the occurrence or existence of another entity or event.
-
D.
hasDisaster
Indicates that an entity experiences, is affected by, or is associated with a disaster event.
-
E.
displacementCause
Indicates a causal relationship where one entity is responsible for the displacement or forced movement of another entity from its original location or situation.
- 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_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdab78832481909b184b21a8a46e50 |
completed | April 1, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69cd03dd2da881909052fbf29736a773 |
completed | April 1, 2026, 11:39 a.m. |
Created at: March 30, 2026, 8:29 p.m.