Triple
T15491761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete’s World |
E378702
|
entity |
| Predicate | hasDifferentFateOfCharacter |
P118455
|
FINISHED |
| Object | Pete Tyler survives and becomes wealthy |
—
|
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: Pete Tyler survives and becomes wealthy | Statement: [Pete’s World, hasDifferentFateOfCharacter, Pete Tyler survives and becomes wealthy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferentFateOfCharacter Context triple: [Pete’s World, hasDifferentFateOfCharacter, Pete Tyler survives and becomes wealthy]
-
A.
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.
-
B.
hasStrangerCharacter
Indicates that one entity possesses or exhibits a character who is a stranger to another entity.
-
C.
isPivotalForCharacter
Indicates that something plays a crucial, defining role in shaping a character’s development, decisions, or narrative arc.
-
D.
hasGhostCharacter
Indicates that an entity includes, features, or is associated with a character that is a ghost.
-
E.
deathInOriginalTimeline
Indicates that an entity dies within the events of the original, unaltered timeline.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:49 a.m.