Triple
T10375905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiez |
E244505
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object | Champvent |
E860318
|
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: Champvent | Statement: [Fiez, hasNeighboringMunicipality, Champvent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Champvent Context triple: [Fiez, hasNeighboringMunicipality, Champvent]
-
A.
Champvent
chosen
Champvent is a small municipality in the canton of Vaud in western Switzerland, known for its rural setting and historic castle.
-
B.
Champ
Champ is a supporting character in the action-spy film "Kingsman: The Golden Circle," serving as a high-ranking member of the American Statesman organization.
-
C.
Champ
Champ is the costumed bulldog mascot representing Louisiana Tech University's athletic teams and school spirit.
-
D.
Champ
Champ is the Dallas Mavericks’ horse-themed team mascot known for energizing crowds at their NBA games.
-
E.
Champ
Champ is the nickname of Champ Clark, an influential early 20th-century American Democratic politician who served as Speaker of the U.S. House of Representatives.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e98278e08190a4d3ff88b4039e49 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d7fb98c52c8190a52682feacc2bd0d |
completed | April 9, 2026, 7:18 p.m. |
Created at: April 6, 2026, 12:02 p.m.