Triple
T37662253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drowned (Minecraft) |
E937741
|
entity |
| Predicate | burnsInDaylightCondition |
P100784
|
FINISHED |
| Object | When not in water or shade |
—
|
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: When not in water or shade | Statement: [Drowned (Minecraft), burnsInDaylightCondition, When not in water or shade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: burnsInDaylightCondition Context triple: [Drowned (Minecraft), burnsInDaylightCondition, When not in water or shade]
-
A.
burnsInDaylight
chosen
Indicates that the subject is harmed, damaged, or destroyed when exposed to daylight.
-
B.
burnsWhen
Indicates that one entity causes another entity to ignite or combust when they come into contact or under specified conditions.
-
C.
burnsIn
Indicates that one entity undergoes combustion or is consumed by fire within or at the location of another entity.
-
D.
burns
Indicates that one entity is consuming or damaging another through fire or intense heat.
-
E.
burnedDuring
Indicates that one event, object, or process was actively burning or being consumed by fire during the time span of another specified event or interval.
- 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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.