Triple
T26892169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carré |
E677205
|
entity |
| Predicate | meaningInFrench |
P57945
|
FINISHED |
| Object | square |
—
|
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: square | Statement: [Carré, meaningInFrench, square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningInFrench Context triple: [Carré, meaningInFrench, square]
-
A.
meaningInArabic
Indicates that one entity expresses the meaning or translation of another entity in the Arabic language.
-
B.
meaningInFinnish
Indicates that one entity expresses the meaning or translation of another entity in the Finnish language.
-
C.
commonNounMeaningInFrench
chosen
Indicates that a common noun has a particular meaning or translation in the French language.
-
D.
meaningInGerman
Indicates that one entity expresses the meaning or translation of another entity in the German language.
-
E.
FrenchSupport
Indicates that one entity provides support, assistance, or backing to another in a specifically French context (e.g., by French actors, in France, or involving the French language or institutions).
- 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_69eee9bc0c90819085608c8bdc513a57 |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f6562fd3488190be1acd8c526a28d2 |
completed | May 2, 2026, 7:53 p.m. |
| PD | Predicate disambiguation | batch_69f651a731508190bb0c8c2462eba224 |
completed | May 2, 2026, 7:33 p.m. |
Created at: April 27, 2026, 5:45 a.m.