Triple
T1303233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John II of Portugal |
E27814
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object |
Alvor
Alvor is a coastal village in Portugal’s Algarve region, known historically as the place where King John II of Portugal died.
|
E148781
|
NE FINISHED |
How this triple was built (4 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: Alvor | Statement: [John II of Portugal, deathPlace, Alvor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alvor Context triple: [John II of Portugal, deathPlace, Alvor]
-
A.
Dokkum
Dokkum is a historic fortified town in the northern Netherlands, known as one of the Frisian Eleven Cities and for its association with the martyrdom of Saint Boniface.
-
B.
Faro
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
C.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
-
D.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
E.
Lillesand
Lillesand is a small coastal town and municipality in Agder county, Norway, known for its white wooden houses, maritime heritage, and popular summer tourism along the Skagerrak coast.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Alvor Triple: [John II of Portugal, deathPlace, Alvor]
Generated description
Alvor is a coastal village in Portugal’s Algarve region, known historically as the place where King John II of Portugal died.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alvor Target entity description: Alvor is a coastal village in Portugal’s Algarve region, known historically as the place where King John II of Portugal died.
-
A.
Dokkum
Dokkum is a historic fortified town in the northern Netherlands, known as one of the Frisian Eleven Cities and for its association with the martyrdom of Saint Boniface.
-
B.
Faro
Faro is a historic coastal city in southern Portugal that serves as the capital of the Algarve region and a major gateway for tourism.
-
C.
Arendal
Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
-
D.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
E.
Lillesand
Lillesand is a small coastal town and municipality in Agder county, Norway, known for its white wooden houses, maritime heritage, and popular summer tourism along the Skagerrak coast.
- F. None of above. chosen
Provenance (5 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c116d7d881908ee631258f80980e |
completed | March 1, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acb3046a888190956f6bedb6ec589f |
completed | March 7, 2026, 11:21 p.m. |
| NEDg | Description generation | batch_69acb370c7cc81908a78bb5438416db6 |
completed | March 7, 2026, 11:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69acb409b4d0819081266cf3e6c09164 |
completed | March 7, 2026, 11:26 p.m. |
Created at: March 1, 2026, 7:51 p.m.