Triple
T8375878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice Tinker |
E197572
|
entity |
| Predicate | hasChildInFiction |
P82383
|
FINISHED |
| Object | multiple children with Hugo Horton |
—
|
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: multiple children with Hugo Horton | Statement: [Alice Tinker, hasChildInFiction, multiple children with Hugo Horton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChildInFiction Context triple: [Alice Tinker, hasChildInFiction, multiple children with Hugo Horton]
-
A.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
B.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
C.
hasGroundsInFiction
Indicates that something is based on, justified by, or finds its origin within fictional works or narratives.
-
D.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
E.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
- 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_69ca82f56730819080cec5d991c76f4c |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80bf6b8081909b98762b1f900bef |
completed | March 31, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69cb70cd04b08190ab5f72afd22a7967 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 6:01 p.m.