Triple
T19294270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Church of Ruoms |
E482520
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Ruoms |
—
|
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: Ruoms | Statement: [Church of Ruoms, locatedIn, Ruoms]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruoms Context triple: [Church of Ruoms, locatedIn, Ruoms]
-
A.
Ruoms
chosen
Ruoms is a small commune in the Ardèche department of southern France, known for its scenic riverside setting and outdoor tourism.
-
B.
Römer
The Römer is Frankfurt am Main’s historic city hall complex, renowned for its distinctive stepped gabled façade and long-standing role as a center of municipal government.
-
C.
Romão
Romão is a Portuguese given name and surname derived from the Latin name Romanus, commonly associated with Roman heritage.
-
D.
Horahane Roma
Horahane Roma are a subgroup of Roma people traditionally associated with Islam and found primarily in regions influenced by the former Ottoman Empire.
-
E.
Romana
Romana is a highly intelligent and compassionate Time Lady from the Doctor Who universe who serves as one of the Doctor’s most capable and scholarly companions.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc84500c81908ac53711335ad2d9 |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.