Triple
T6706876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Yasur |
E153028
|
entity |
| Predicate | hasFrequentExplosions |
P72551
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Mount Yasur, hasFrequentExplosions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequentExplosions Context triple: [Mount Yasur, hasFrequentExplosions, yes]
-
A.
numberOfExplosions
Indicates the count of distinct explosion events associated with an entity or situation.
-
B.
numberOfFailedBombs
Indicates the count of bombs associated with an entity that did not successfully detonate or function as intended.
-
C.
explosiveClass
Indicates the classification or category assigned to an explosive based on its type, properties, or regulatory class.
-
D.
detonatedOver
Indicates that one entity caused an explosion or detonation to occur above or over another entity or location.
-
E.
depictsExplosion
Indicates that one entity visually represents or portrays an explosion involving another entity or within a scene.
- 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_69c68808d8d8819087369015270788fe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16897e48190b43eda2206b14d6a |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d089c7488190a00853fb12f53b2a |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d1668a7c8190ae93951f9ba2df10 |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:06 p.m.