Triple
T12391548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sammy Jankis |
E296004
|
entity |
| Predicate | hasTragicArc |
P101514
|
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: [Sammy Jankis, hasTragicArc, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTragicArc Context triple: [Sammy Jankis, hasTragicArc, true]
-
A.
hasTragicEnding
Indicates that the event, story, or situation concludes with a sorrowful, disastrous, or otherwise deeply unfortunate outcome.
-
B.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
-
C.
characterArcOutcome
chosen
Indicates the resulting change, resolution, or final state of a character’s personal journey or development over the course of a narrative.
-
D.
hasHappyEnding
Indicates that the event, story, or situation concludes with a positive, satisfying, or favorable outcome for the involved entities.
-
E.
hasProtagonistJourneyType
Indicates that a narrative work features a main character whose overarching journey follows a specific type or pattern (e.g., hero’s journey, coming-of-age, tragedy).
- F. None of above.
Provenance (3 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fd0bcc48190bb1a59a3aaa6bfdf |
completed | April 10, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.