Triple
T10582586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keres |
E249771
|
entity |
| Predicate | differenceFromThanatos |
P94764
|
FINISHED |
| Object | represent violent and bloody death rather than peaceful 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: represent violent and bloody death rather than peaceful death | Statement: [Keres, differenceFromThanatos, represent violent and bloody death rather than peaceful death]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differenceFromThanatos Context triple: [Keres, differenceFromThanatos, represent violent and bloody death rather than peaceful death]
-
A.
deathPrecedes
Indicates that one entity’s death occurs earlier in time than another specified event or entity’s death.
-
B.
afterDeath
Indicates that one event, state, or condition occurs subsequent to and as a result of an entity’s death.
-
C.
deathBefore
Indicates that one entity’s death occurred earlier in time than another entity’s death.
-
D.
deathDescribedAs
Indicates that one entity characterizes, portrays, or refers to another entity’s death using a particular description, metaphor, or wording.
-
E.
death
Indicates the event or state in which an entity ceases to live or exist, marking the end of its biological or functional processes.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d52766d53c8190b51753768ab58c31 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
| PDg | Predicate description generation | batch_69d5270eca0481908573b698390c5b08 |
completed | April 7, 2026, 3:47 p.m. |
Created at: April 6, 2026, 12:39 p.m.