Triple
T11117166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usquert |
E262915
|
entity |
| Predicate | hasRegion |
P285
|
FINISHED |
| Object | Hogeland |
E50238
|
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: Hogeland | Statement: [Usquert, hasRegion, Hogeland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hogeland Context triple: [Usquert, hasRegion, Hogeland]
-
A.
Hageland
Hageland is a hilly, rural region in the eastern part of Flemish Brabant in Belgium, known for its orchards, vineyards, and scenic landscapes.
-
B.
Het Hogeland
chosen
Het Hogeland is a coastal municipality in the northern Netherlands known for its open landscapes, historic villages, and Wadden Sea shoreline.
-
C.
Haardt
Haardt is a district of Neustadt an der Weinstraße in Rhineland-Palatinate, Germany, known for its scenic location along the German Wine Route and proximity to the Palatinate Forest.
-
D.
Wheatland
Wheatland is a small incorporated city in Northern California known for its agricultural surroundings and location within Yuba County.
-
E.
Hooperman
Hooperman is an American television dramedy series from the late 1980s starring John Ritter as a San Francisco police inspector balancing his personal and professional life.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79af638b08190b7ade5eb0cab6b75 |
completed | April 9, 2026, 12:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ace2228c8190936757f5b1eaa1eb |
completed | April 19, 2026, 10:22 a.m. |
Created at: April 8, 2026, 9:27 p.m.