Triple
T8750779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Iowa |
E207951
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Panora |
E712842
|
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: Panora | Statement: [Central Iowa, hasCity, Panora]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panora Context triple: [Central Iowa, hasCity, Panora]
-
A.
Panora
chosen
Panora is a small city in central Iowa known for its proximity to Lake Panorama and its role as a local hub within Guthrie County.
-
B.
Panorama
Panorama is a long-running BBC television current affairs documentary programme known for its investigative journalism and in-depth reporting on political and social issues.
-
C.
Panorama
Panorama is a prominent sidebar section of the Berlin International Film Festival that showcases innovative, independent, and socially engaged films from around the world.
-
D.
Panorama
Panorama is a notable musical number from the stage musical "The Sleeping Beauty."
-
E.
Passage des Panoramas
Passage des Panoramas is one of Paris’s oldest covered shopping arcades, known for its 19th-century charm, small boutiques, and traditional cafés.
- 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_69ca835bb2bc819084bb5906cb6ef7f8 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5da774f4819099e5bfd12973d946 |
completed | March 31, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf431db5a88190a579b43370a8e887 |
completed | April 3, 2026, 4:33 a.m. |
Created at: March 30, 2026, 6:39 p.m.