Triple
T22245765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napoleon death mask |
E549836
|
entity |
| Predicate | timeSinceSubjectDeath |
P147533
|
FINISHED |
| Object | taken shortly after Napoleon’s death |
—
|
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: taken shortly after Napoleon’s death | Statement: [Napoleon death mask, timeSinceSubjectDeath, taken shortly after Napoleon’s death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSinceSubjectDeath Context triple: [Napoleon death mask, timeSinceSubjectDeath, taken shortly after Napoleon’s death]
-
A.
timeBeforeDeath
Indicates that the associated time value occurs prior to an entity’s death or moment of dying.
-
B.
timeOfDeath
Indicates the specific time at which an entity (typically a person or organism) died.
-
C.
timeInTomb
Indicates the duration that an entity remains or has remained inside a tomb.
-
D.
diedAfter
Indicates that one entity’s death occurred later in time than another entity’s death.
-
E.
timeBetweenInjuryAndDeath
Indicates the duration of time that elapses between when an injury occurs and when death subsequently happens.
- 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_69e11e41d9408190bd770cf282e22753 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f13217c9f88190aa2ce7d644b57739 |
completed | April 28, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69e72fe1e0cc8190bd13cff2a0846225 |
completed | April 21, 2026, 8:05 a.m. |
| PDg | Predicate description generation | batch_69e7342ce08c8190bc0a7085f4a952e7 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:38 p.m.