Triple
T20650497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mrs Wilson |
E507476
|
entity |
| Predicate | isBasedOnTrueStory |
P93832
|
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: [Mrs Wilson, isBasedOnTrueStory, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isBasedOnTrueStory Context triple: [Mrs Wilson, isBasedOnTrueStory, true]
-
A.
basedOnRealLife
chosen
Indicates that something is derived from, inspired by, or directly adapted from actual real-world events, people, or situations.
-
B.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
C.
usesRealHistoricalEvents
Indicates that the subject incorporates or is based on actual events that occurred in real history.
-
D.
historicallyBasedOn
Indicates that something is derived from, inspired by, or modeled on historical events, sources, or precedents.
-
E.
hasFictionalBackstory
Indicates that an entity is associated with an invented or imaginary narrative background rather than a real-world history.
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af2133048190a6308074a3b3347e |
completed | April 20, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69e5c0315f5081908098707c6455e56e |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 11:43 a.m.