Triple
T27987427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portraits of Ernest Hemingway |
E706779
|
entity |
| Predicate | subjectAssociatedPlace |
P112751
|
FINISHED |
| Object | Paris |
—
|
NE NERFINISHED |
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: Paris | Statement: [Portraits of Ernest Hemingway, subjectAssociatedPlace, Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAssociatedPlace Context triple: [Portraits of Ernest Hemingway, subjectAssociatedPlace, Paris]
-
A.
personAssociatedPlace
chosen
Indicates that a person has a notable connection or association with a particular place, such as residence, origin, work, or frequent presence.
-
B.
relatedPlace
Indicates a relationship where one place is connected or associated with another place in a relevant or meaningful way.
-
C.
positionAssociatedWith
Indicates a relationship where a specific role, job, or position is linked or connected to a particular entity, context, or resource.
-
D.
subjectLocation
Indicates that one entity is located at, in, or near the place or position specified by another entity.
-
E.
organizationAssociatedWith
Indicates that there is a formal or recognized connection or affiliation between an organization and another entity.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 27, 2026, 7:48 p.m.