Triple
T15887862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aegidius |
E385235
|
entity |
| Predicate | patronage |
P2320
|
FINISHED |
| Object | Toulon |
E83956
|
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: Toulon | Statement: [Aegidius, patronage, Toulon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toulon Context triple: [Aegidius, patronage, Toulon]
-
A.
Toulon
chosen
Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
-
B.
La Rochelle
La Rochelle is a historic French Atlantic port city that became a major stronghold and refuge for Huguenots during the French Wars of Religion.
-
C.
Toulouse
"Toulouse" is a popular 2011 electro house track by Dutch DJ and producer Nicky Romero that helped establish his international reputation in the EDM scene.
-
D.
Toulouse
Toulouse is a fictional orange kitten from Disney's animated film "The Aristocats," known for his playful, boisterous personality and admiration of alley cats.
-
E.
Toulouse
Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
- 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_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1561c3d008190a892f091a2f874cf |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb59f979c8190826e35a16e295704 |
completed | May 9, 2026, 10:30 p.m. |
Created at: April 10, 2026, 4:51 a.m.