Triple
T19188600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panopolis |
E469768
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Chemmis |
—
|
NE NERFINISHED |
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: Chemmis | Statement: [Panopolis, knownAs, Chemmis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chemmis Context triple: [Panopolis, knownAs, Chemmis]
-
A.
Chemmis
chosen
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.
-
B.
Chemici
Chemici is the nickname of the Czech ice hockey club HC Litvínov, reflecting the town’s strong chemical industry heritage.
-
C.
Chemal
Chemal is a village and popular tourist destination in Russia’s Altai Republic, known for its scenic mountain landscapes along the Katun River and outdoor recreation opportunities.
-
D.
Chamical
Chamical is a small city in central La Rioja Province, Argentina, known historically as a regional railway and agricultural center.
-
E.
Challex
Challex is a small commune in eastern France’s Ain department, near the Swiss border in the Auvergne-Rhône-Alpes region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a01d08819081608a6ab8c6e705 |
completed | April 20, 2026, 9:57 a.m. |
Created at: April 10, 2026, 12:07 p.m.