Triple
T6762281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vegårshei |
E154623
|
entity |
| Predicate | adminCenter |
P3892
|
FINISHED |
| Object | Myra |
E220346
|
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: Myra | Statement: [Vegårshei, adminCenter, Myra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myra Context triple: [Vegårshei, adminCenter, Myra]
-
A.
Myra
Myra is a feminine given name used in various cultures, often associated with individuals of Jewish and English-speaking backgrounds.
-
B.
Myra
chosen
Myra was an ancient Greek city in Lycia, in what is now southwestern Turkey, historically notable as a major early Christian center and the bishopric of Saint Nicholas.
-
C.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
D.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
-
E.
Sarina
Sarina is a Dutch football manager and former player best known for coaching top international women’s national teams, including the Netherlands and England.
- 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_69c688109c1c8190added9a221292af0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d21444dc8190a290af86c81e96a5 |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712b6ec408190bd9131f289b02ba7 |
completed | March 27, 2026, 11:28 p.m. |
Created at: March 27, 2026, 2:12 p.m.