Triple
T3238004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mogadishu Cathedral (ruins) |
E67899
|
entity |
| Predicate | partlyDemolishedBy |
P17180
|
FINISHED |
| Object | Al-Shabaab militants |
—
|
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: Al-Shabaab militants | Statement: [Mogadishu Cathedral (ruins), partlyDemolishedBy, Al-Shabaab militants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partlyDemolishedBy Context triple: [Mogadishu Cathedral (ruins), partlyDemolishedBy, Al-Shabaab militants]
-
A.
partlyDismantledBy
chosen
Indicates that an entity has been only partially taken apart, removed, or deconstructed by another agent or process.
-
B.
partiallyDestroyed
Indicates that an entity has been damaged or ruined to a significant extent but not completely destroyed.
-
C.
hasDemolitionOrDestruction
Indicates that one entity causes, undergoes, or is associated with the demolition or destruction of another entity.
-
D.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
E.
demolished
Indicates that one entity completely destroyed or razed another entity, typically a structure or object, so that it no longer exists in its previous form.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef3b04081908ce9b788e2e5c63c |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ada4159e0481908cbbdd750f5e08c7 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:08 p.m.