Triple
T6469087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warehouse 12 at Port of Beirut |
E142301
|
entity |
| Predicate | consequenceOfExplosion |
P70979
|
FINISHED |
| Object | major destruction in surrounding port area |
—
|
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: major destruction in surrounding port area | Statement: [Warehouse 12 at Port of Beirut, consequenceOfExplosion, major destruction in surrounding port area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consequenceOfExplosion Context triple: [Warehouse 12 at Port of Beirut, consequenceOfExplosion, major destruction in surrounding port area]
-
A.
consequenceOfDestruction
Indicates that one event, state, or condition occurs as a direct result of a prior act of destruction.
-
B.
resultOfBombing
Indicates that something exists or occurs as a consequence or outcome of a bombing event.
-
C.
detonatedOver
Indicates that one entity caused an explosion or detonation to occur above or over another entity or location.
-
D.
depictsExplosion
Indicates that one entity visually represents or portrays an explosion involving another entity or within a scene.
-
E.
numberOfExplosions
Indicates the count of distinct explosion events associated with an entity or situation.
- F. None of above. chosen
Provenance (4 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_69c008d3bf4c8190bcf798c5ba9d6fb3 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06a16272c81909313455002cd884d |
completed | March 22, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69c0673d46a08190bc8bcd29f9555fe7 |
completed | March 22, 2026, 10:03 p.m. |
| PDg | Predicate description generation | batch_69c067da970481908a038995ba7dfb4b |
completed | March 22, 2026, 10:06 p.m. |
Created at: March 22, 2026, 4:49 p.m.