Triple
T12504315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chamical Department |
E298907
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Chamical |
E298902
|
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: Chamical | Statement: [Chamical Department, hasCapital, Chamical]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chamical Context triple: [Chamical Department, hasCapital, Chamical]
-
A.
Chamical
chosen
Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
-
B.
Noxon
Noxon is a surname most notably associated with American television writer, producer, and director Marti Noxon.
-
C.
Chemmis
Chemmis is the ancient Greek name for the Egyptian city of Akhmim, a historically significant settlement in Upper Egypt known for its temples and religious heritage.
-
D.
Challex
Challex is a small commune in eastern France’s Ain department, near the Swiss border in the Auvergne-Rhône-Alpes region.
-
E.
Carbone
Carbone is a high-end Italian-American restaurant known for its classic New York red-sauce dishes and retro, mid-20th-century ambiance.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfcea188190a929db1aabe1a286 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb5af708190b3786da334c3bf23 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:57 p.m.