Triple
T10513166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Die |
E247966
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Die |
E242861
|
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: Die | Statement: [Arrondissement of Die, seat, Die]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Die Context triple: [Arrondissement of Die, seat, Die]
-
A.
Die
chosen
Die is a historic commune in southeastern France known for its medieval architecture and as a center of the Clairette de Die sparkling wine region.
-
B.
Toten
Toten is a traditional rural district in eastern Norway known for its agriculture and scenic landscape, located within Innlandet county.
-
C.
Der
Der was an ancient Mesopotamian city known as an important religious center associated with the worship of the god Anu.
-
D.
Dead
Dead is the surname of the central African American family in Toni Morrison’s novel "Song of Solomon," most notably borne by the protagonist Milkman Dead.
-
E.
Dar
Dar is the warrior protagonist and titular Beastmaster of the Beastmaster fantasy franchise, known for his ability to telepathically communicate with and command animals.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509ca214481909b3ed9265e7a6704 |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b13f4fc8190863d6e1aa7da5733 |
completed | April 10, 2026, 7:10 p.m. |
Created at: April 6, 2026, 12:27 p.m.