Triple
T1746705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alentejo |
E38350
|
entity |
| Predicate | bordersRegion |
P224
|
FINISHED |
| Object | Lisbon Region |
E128968
|
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: Lisbon Region | Statement: [Alentejo, bordersRegion, Lisbon Region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lisbon Region Context triple: [Alentejo, bordersRegion, Lisbon Region]
-
A.
Lisbon District
chosen
Lisbon District is an administrative region in central-western Portugal that includes the nation’s capital, Lisbon, and several surrounding municipalities.
-
B.
Alentejo
Alentejo is a large, sparsely populated region in southern Portugal known for its rolling plains, cork oak forests, vineyards, and historic whitewashed towns.
-
C.
Évora District
Évora District is an administrative region in southern Portugal known for its historic city of Évora, a UNESCO World Heritage site rich in Roman and medieval heritage.
-
D.
Coimbra District
Coimbra District is an administrative region in central Portugal that includes the historic university city of Coimbra and surrounding municipalities.
-
E.
Algarve
Algarve is a popular coastal region in southern Portugal known for its beaches, cliffs, and resort towns.
- 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_69a8862b01a48190ab47209063af82d9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa63eabdf48190878ecde3d1b1faf3 |
completed | March 6, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeaca5f348190a8c1be9948d960e6 |
completed | March 8, 2026, 9:31 p.m. |
Created at: March 4, 2026, 7:31 p.m.