Triple
T16648717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Act Tragedy |
E404543
|
entity |
| Predicate | hasMurderer |
P124122
|
FINISHED |
| Object | stage actor (identity revealed in novel) |
—
|
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: stage actor (identity revealed in novel) | Statement: [Three Act Tragedy, hasMurderer, stage actor (identity revealed in novel)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMurderer Context triple: [Three Act Tragedy, hasMurderer, stage actor (identity revealed in novel)]
-
A.
hasPartInMurderOf
Indicates involvement as a contributing participant in the commission of a murder.
-
B.
hasMurderVictimCharacter
Indicates that an entity (such as a work of fiction or event) includes or involves a character who is the victim of a murder.
-
C.
hasSerialKiller
Indicates that one entity is a serial killer associated with, responsible for, or targeting another entity.
-
D.
hasKiller
Indicates that one entity is the killer or cause of death of another entity.
-
E.
hasMannerOfDeath
Indicates the specific way or circumstances in which an entity died, such as natural causes, accident, homicide, or suicide.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ad794388190b2817d2ec5ff0de0 |
completed | April 18, 2026, 12:36 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:18 a.m.