Triple
T8098529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Nivelles |
E189046
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Hélécine |
E696209
|
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: Hélécine | Statement: [Arrondissement of Nivelles, containsMunicipality, Hélécine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hélécine Context triple: [Arrondissement of Nivelles, containsMunicipality, Hélécine]
-
A.
Hélécine
chosen
Hélécine is a small rural municipality in the province of Walloon Brabant in Wallonia, Belgium.
-
B.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
C.
Benthesikyme
Benthesikyme is a minor sea goddess in Greek mythology, known primarily as a daughter of Poseidon.
-
D.
Cérons
Cérons is a French wine appellation in the Graves region of Bordeaux, known for its sweet white wines made primarily from Semillon, Sauvignon Blanc, and Muscadelle grapes.
-
E.
Agathé
Agathé is the ancient Greek name for the historic Mediterranean port city now known as Agde in southern France.
- 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_69ca82b886d88190a9cba0d5a4a27521 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42961ad4819085d023427fc5ac5f |
completed | March 31, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc641a4b4881908a1aec4bc2ed619e |
completed | April 1, 2026, 12:17 a.m. |
Created at: March 30, 2026, 5:30 p.m.