Triple
T8844057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IJsselmonde |
E210458
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Lombardijen
Lombardijen is a residential neighborhood in the IJsselmonde borough of Rotterdam in the Netherlands.
|
E760239
|
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: Lombardijen | Statement: [IJsselmonde, hasSubdivision, Lombardijen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lombardijen Context triple: [IJsselmonde, hasSubdivision, Lombardijen]
-
A.
Massa Lombarda
Massa Lombarda is a small Italian town in the Emilia-Romagna region, known for its agricultural traditions and location within the fertile Po Valley.
-
B.
Lombard
Lombard is a Gallo-Italic Romance language traditionally spoken in and around Milan and across much of Lombardy in northern Italy.
-
C.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
-
D.
Nursia
Nursia is an ancient town in central Italy, historically significant as the birthplace of Saint Benedict and known today as Norcia.
-
E.
Sansobbia
Sansobbia is a small river in the Liguria region of northwestern Italy that flows through the municipality of Albisola Superiore before reaching the Ligurian Sea.
- 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: Lombardijen Triple: [IJsselmonde, hasSubdivision, Lombardijen]
Generated description
Lombardijen is a residential neighborhood in the IJsselmonde borough of Rotterdam in the Netherlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lombardijen Target entity description: Lombardijen is a residential neighborhood in the IJsselmonde borough of Rotterdam in the Netherlands.
-
A.
Massa Lombarda
Massa Lombarda is a small Italian town in the Emilia-Romagna region, known for its agricultural traditions and location within the fertile Po Valley.
-
B.
Lombard
Lombard is a Gallo-Italic Romance language traditionally spoken in and around Milan and across much of Lombardy in northern Italy.
-
C.
Senigallia
Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
-
D.
Nursia
Nursia is an ancient town in central Italy, historically significant as the birthplace of Saint Benedict and known today as Norcia.
-
E.
Sansobbia
Sansobbia is a small river in the Liguria region of northwestern Italy that flows through the municipality of Albisola Superiore before reaching the Ligurian Sea.
- 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_69ca838967bc8190b46c3c80a2887ea4 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc608a73c88190875409fef79ffc8a |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf89ad0a3c8190a2bcf9a106138835 |
completed | April 3, 2026, 9:34 a.m. |
| NEDg | Description generation | batch_69cf8ac657a48190b01e3f0365105f3c |
completed | April 3, 2026, 9:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf8b8849ec8190915fa087b1b46c18 |
completed | April 3, 2026, 9:42 a.m. |
Created at: March 30, 2026, 6:48 p.m.