Triple
T10225577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Leftovers |
E243194
|
entity |
| Predicate | percentageOfWorldPopulationDisappearedInFiction |
P92862
|
FINISHED |
| Object | 2% |
—
|
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: 2% | Statement: [The Leftovers, percentageOfWorldPopulationDisappearedInFiction, 2%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageOfWorldPopulationDisappearedInFiction Context triple: [The Leftovers, percentageOfWorldPopulationDisappearedInFiction, 2%]
-
A.
populationAfterDestruction
Indicates the size or composition of a population following an event of destruction or devastation.
-
B.
fictionalPopulation
Indicates that a location or setting has an imagined or non-real population, as found in fictional works.
-
C.
populationLoss
Indicates a decrease in the number of individuals within a defined population over a given period or due to specific causes.
-
D.
deathInFiction
Indicates that an entity’s death occurs within a fictional work or narrative rather than in real life.
-
E.
coversShareOfWorldPopulation
Indicates that something accounts for or includes a specified proportion of the total human population worldwide.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d23a9c4c8190abece9e52879c479 |
completed | April 7, 2026, 9:45 a.m. |
Created at: April 6, 2026, 11:17 a.m.