Triple
T18585295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auxerrois |
E454221
|
entity |
| Predicate | alsoDenotes |
P63266
|
FINISHED |
| Object | things associated with Auxerre |
—
|
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: things associated with Auxerre | Statement: [Auxerrois, alsoDenotes, things associated with Auxerre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoDenotes Context triple: [Auxerrois, alsoDenotes, things associated with Auxerre]
-
A.
alsoRefersTo
chosen
Indicates that one term, label, or identifier is used as an alternative designation for the same entity or concept as another.
-
B.
alsoIn
Indicates that an entity participates in or belongs to an additional context, group, or location alongside another already specified one.
-
C.
alsoServesAs
Indicates that one entity has an additional role, function, or identity that it fulfills simultaneously with its primary one.
-
D.
denominates
Indicates that one entity serves as the official name, designation, or label for another entity.
-
E.
alsoKnownThrough
Indicates that an entity is recognized or identified by means of another entity, such as a source, context, or intermediary, through which its alternative name or identity is known.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b0dff08190a3be481faec34a3c |
completed | April 19, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:44 a.m.