Triple
T1781673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beja District |
E39302
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Moura |
E201551
|
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: Moura | Statement: [Beja District, containsTown, Moura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moura Context triple: [Beja District, containsTown, Moura]
-
A.
Moura
chosen
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
B.
Myra
Myra is a feminine given name used in various cultures, often associated with individuals of Jewish and English-speaking backgrounds.
-
C.
Terevaka
Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
-
D.
Arida
Arida is a city in Japan known for its agricultural production, particularly high-quality citrus fruits, within Wakayama Prefecture.
-
E.
Coruripe
Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
- 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64e34fe881908aa75f2b4141b87b |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf3d06e88190a082b142ff9209ee |
completed | March 8, 2026, 8:42 p.m. |
Created at: March 4, 2026, 7:31 p.m.