Triple
T13048506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Condroz |
E327385
|
entity |
| Predicate | containsSettlement |
P847
|
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: [Condroz, containsSettlement, Hélécine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hélécine Context triple: [Condroz, containsSettlement, 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.
Ousanas
Ousanas was a king of the ancient Kingdom of Aksum in what is now Ethiopia, known from inscriptions and coinage as an early Christian-era ruler preceding King Ezana.
-
E.
Darphin
Darphin is a French luxury skincare brand renowned for its botanically based, spa-inspired treatments and high-performance serums.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b8811c81908577f092e2736610 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:57 p.m.