Triple
T6179927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgae |
E137915
|
entity |
| Predicate | subTribe |
P29097
|
FINISHED |
| Object | Remi |
E192207
|
NE 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: Remi | Statement: [Belgae, subTribe, Remi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Remi Context triple: [Belgae, subTribe, Remi]
-
A.
Remi
chosen
The Remi were a Belgic tribe of northeastern Gaul known for allying with Julius Caesar during the Gallic Wars.
-
B.
Felix
Felix is a masculine given name of Latin origin meaning "happy" or "fortunate," borne by numerous historical and contemporary figures.
-
C.
Zibelle
Zibelle is a village in eastern Germany, historically part of Lusatia, known in this context as the place where physicist Walther Nernst died.
-
D.
Ratonneau
Ratonneau is one of the main islands of the Frioul archipelago off the coast of Marseille in southern France, known for its rocky landscapes and Mediterranean coves.
-
E.
Remy
Remy is the ambitious, food-loving rat and main protagonist of Pixar’s animated film "Ratatouille," known for his exceptional culinary talent and dream of becoming a chef in Paris.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008a80f748190ba3d07ffc81acb29 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05dcb77948190b5385438f81bf0a8 |
completed | March 22, 2026, 9:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c141bf3f4081909849e38d322da251 |
completed | March 23, 2026, 1:35 p.m. |
Created at: March 22, 2026, 4:18 p.m.