Triple
T9299633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guarda District |
E223725
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Seia |
E374150
|
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: Seia | Statement: [Guarda District, containsMunicipality, Seia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seia Context triple: [Guarda District, containsMunicipality, Seia]
-
A.
Seia
chosen
Seia is a municipality and town in central Portugal known for its proximity to the Serra da Estrela mountains and natural park.
-
B.
Reona
Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
-
C.
Geisa
Geisa is a small historic town in the state of Thuringia in central Germany, near the former inner-German border.
-
D.
Seika
Seika is a town in Kyoto Prefecture, Japan, known for its residential communities and proximity to the Kansai Science City area.
-
E.
Meya
Meya is a variant form of the given name Maya, often used as a feminine personal name.
- 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_69ca8423edb08190bc0c91287a484768 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d070c881908bed41aada6f85ae |
completed | April 1, 2026, noon |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b25ac97881908751b466b370b7e5 |
completed | April 4, 2026, 6:40 a.m. |
Created at: March 30, 2026, 7:36 p.m.