Triple
T16030700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vrachionas |
E388837
|
entity |
| Predicate | hasRoadAccessFrom |
P22549
|
FINISHED |
| Object | Maries |
E1188892
|
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: Maries | Statement: [Vrachionas, hasRoadAccessFrom, Maries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maries Context triple: [Vrachionas, hasRoadAccessFrom, Maries]
-
A.
Maries
chosen
Maries is a small village on the Greek island of Zakynthos, known for its traditional character and proximity to the island’s mountainous interior.
-
B.
Macaria
Macaria is a figure in Greek mythology known as a daughter of Heracles, associated with themes of sacrifice and deliverance.
-
C.
Maira
Maira is a given name used in various cultures, often as a variant of names like Maera, Maria, or Mary.
-
D.
Mariann
Mariann is the given name of Mariann Edgar Budde, an American Episcopal bishop known for her leadership in the Episcopal Diocese of Washington.
-
E.
Mariani
Mariani is a town in Assam, India, known as a key railway hub in the region.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1832b0f308190a23edfaf55f3ca25 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbd1cafc81909125174eed475d55 |
completed | May 10, 2026, 1:13 a.m. |
Created at: April 10, 2026, 4:56 a.m.