Triple
T23194644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Humen Opium Destruction |
E579840
|
entity |
| Predicate | quantityDestroyed |
P151306
|
FINISHED |
| Object | over 20,000 chests of opium |
—
|
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: over 20,000 chests of opium | Statement: [Humen Opium Destruction, quantityDestroyed, over 20,000 chests of opium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quantityDestroyed Context triple: [Humen Opium Destruction, quantityDestroyed, over 20,000 chests of opium]
-
A.
weaponDestroyed
Indicates that a weapon has been rendered unusable or eliminated, typically as a result of some action or event.
-
B.
estimatedTeaChestsDestroyed
Indicates the estimated number of tea chests that were destroyed in a given event or context.
-
C.
estimatedNumberOfBooksDestroyed
Indicates the approximate quantity of books that were destroyed in a given event or context.
-
D.
timeOfDestruction
Indicates the specific time at which an entity is destroyed or ceases to exist.
-
E.
sufferedDestructionOf
Indicates that one entity experienced damage, ruin, or loss as a result of the destruction of another entity.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fda64cc8190aeb5ccd8d8d20858 |
completed | April 29, 2026, 4:58 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b75e2708190ba48875e36f983bc |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 4:06 p.m.