Triple
T13831485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moroccan |
E332408
|
entity |
| Predicate | spelledInFrench |
P6538
|
FINISHED |
| Object | Marocain |
—
|
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: Marocain | Statement: [Moroccan, spelledInFrench, Marocain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spelledInFrench Context triple: [Moroccan, spelledInFrench, Marocain]
-
A.
isFrancophoneCounterpartOf
Indicates that one entity serves as the French-speaking or French-language equivalent or counterpart of another entity.
-
B.
nameInFrench
chosen
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
C.
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).
-
D.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
-
E.
usesPrimaryFrenchGateway
Indicates that an entity routes its primary communications or connections through a main gateway located in or associated with French infrastructure or networks.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0299334481908c2b271eaf06e4b7 |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.