Triple
T36919172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essential Killing |
E913131
|
entity |
| Predicate | hasNoConventionalBackstory |
P205637
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Essential Killing, hasNoConventionalBackstory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoConventionalBackstory Context triple: [Essential Killing, hasNoConventionalBackstory, true]
-
A.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
-
B.
hasNoConventionalProtagonist
Indicates that a narrative work lacks a single, traditional central hero or main character driving the story.
-
C.
hasOrphanProtagonist
Indicates that the main character in a work is an orphan, lacking one or both parents as part of the story’s premise.
-
D.
hasNoHumanProtagonist
Indicates that in the described work or narrative, none of the main protagonists are human characters.
-
E.
hasMysteriousPast
Indicates that an entity possesses a past that is unknown, hidden, or only partially revealed, often implying secrets or unexplained events.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:13 p.m.