Triple
T37798232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellie Burr |
E942293
|
entity |
| Predicate | isYoungDetective |
P80419
|
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: [Ellie Burr, isYoungDetective, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isYoungDetective Context triple: [Ellie Burr, isYoungDetective, true]
-
A.
hasClericalDetective
Indicates that an entity includes or is associated with a detective who is also a member of the clergy.
-
B.
hasFictionalDetective
Indicates that one entity (typically a work or series) features or includes a fictional detective character as part of its content.
-
C.
isYoung
Indicates that an entity is at an early stage of life or development relative to a relevant norm or comparison group.
-
D.
detectiveType
chosen
Indicates that one entity is classified as a particular type or category of detective in relation to another entity.
-
E.
skillLevelAsDetective
Indicates the degree or proficiency of an entity in performing detective-related tasks or investigative work.
- 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_69f76ee6f1f4819091e2cf9c9e6aee19 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:19 p.m.