Triple
T10429717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aremark Church |
E245878
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Aremark |
E50823
|
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: Aremark | Statement: [Aremark Church, locatedIn, Aremark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aremark Context triple: [Aremark Church, locatedIn, Aremark]
-
A.
Aremark
chosen
Aremark is a small rural municipality in southeastern Norway known for its forests, lakes, and outdoor recreation.
-
B.
Amm
Amm is an ancient South Arabian god, particularly revered in the Qataban kingdom as a principal deity associated with protection and tribal identity.
-
C.
Ateste
Ateste is the ancient name of the Italian town of Este, historically significant as a center of the Venetic civilization in northern Italy.
-
D.
Ant
Ant is a Java-based build automation tool commonly used to compile, package, and deploy Java applications using XML configuration files.
-
E.
Auch
Auch is a historic town in southwestern France that serves as the capital of the Gers department and is known for its cathedral and medieval old town.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea62d6448190a7f5b785467824cf |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94afc8ef0819093791447d3c3c018 |
completed | April 10, 2026, 7:09 p.m. |
Created at: April 6, 2026, 12:13 p.m.