Triple
T28103604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attikamek |
E710302
|
entity |
| Predicate | peopleNameInFrench |
P6538
|
FINISHED |
| Object | Attikamek |
—
|
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: Attikamek | Statement: [Attikamek, peopleNameInFrench, Attikamek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peopleNameInFrench Context triple: [Attikamek, peopleNameInFrench, Attikamek]
-
A.
nameInFrench
chosen
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
B.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
C.
FrenchNameMeaning
Indicates that the relationship specifies the meaning or etymological sense of a given French name.
-
D.
FrenchForm
Indicates that one entity is a form, version, or expression of another specifically in the French language.
-
E.
hasFrenchWikipediaPage
Indicates that the subject entity has a dedicated article on the French-language version of Wikipedia.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f64093968c8190a76fb2261ed9f0a8 |
completed | May 2, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69f63c6a8474819091b8c6fe98e3862d |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 9:06 p.m.