Triple
T2351670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amy March |
E47460
|
entity |
| Predicate | notableTraitInChildhood |
P37384
|
FINISHED |
| Object | mispronounces words |
—
|
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: mispronounces words | Statement: [Amy March, notableTraitInChildhood, mispronounces words]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableTraitInChildhood Context triple: [Amy March, notableTraitInChildhood, mispronounces words]
-
A.
spentChildhoodIn
Indicates that a person or entity spent the majority or formative years of their childhood in a particular place or location.
-
B.
children
Indicates that one entity is the offspring or direct descendant of another entity.
-
C.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
-
D.
diedInChildhood
Indicates that the person died before reaching adulthood, during their childhood years.
-
E.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
- 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_69a88a1b678c8190bce986922ba60ce0 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abcb802da08190980100444010f91e |
completed | March 7, 2026, 6:53 a.m. |
| PD | Predicate disambiguation | batch_69abc5981ce48190a3f7852d28276e11 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:54 p.m.