Triple
T5749721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antwerp Province |
E126820
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Geel
Geel is a city in the Flemish region of Belgium, noted for its long-standing tradition of community-based psychiatric care.
|
E543565
|
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: Geel | Statement: [Antwerp Province, contains, Geel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geel Context triple: [Antwerp Province, contains, Geel]
-
A.
Gelb
Gelb is a surname most prominently associated with Peter Gelb, the influential general manager of the Metropolitan Opera in New York City.
-
B.
Groen
Groen is a Flemish green political party in Belgium known for its progressive stance on environmental and social issues.
-
C.
Rood-witten
Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
-
D.
Rood
Rood is a surname most notably associated with Ogden Rood, an American physicist and color theorist known for his influential work on color science.
-
E.
Geel-zwarten
Geel-zwarten is a common Dutch nickname referring to the football club Vitesse, derived from the team’s yellow-and-black colors.
- 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: Geel Triple: [Antwerp Province, contains, Geel]
Generated description
Geel is a city in the Flemish region of Belgium, noted for its long-standing tradition of community-based psychiatric care.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Geel Target entity description: Geel is a city in the Flemish region of Belgium, noted for its long-standing tradition of community-based psychiatric care.
-
A.
Gelb
Gelb is a surname most prominently associated with Peter Gelb, the influential general manager of the Metropolitan Opera in New York City.
-
B.
Groen
Groen is a Flemish green political party in Belgium known for its progressive stance on environmental and social issues.
-
C.
Rood-witten
Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
-
D.
Rood
Rood is a surname most notably associated with Ogden Rood, an American physicist and color theorist known for his influential work on color science.
-
E.
Geel-zwarten
Geel-zwarten is a common Dutch nickname referring to the football club Vitesse, derived from the team’s yellow-and-black colors.
- 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_69c00832aedc81909899801b141fa3b4 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0288870fc819080e883c9d589359b |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07e358d908190a37e5df89df3aedc |
completed | March 22, 2026, 11:41 p.m. |
| NEDg | Description generation | batch_69c089020764819090a1927c65f9e870 |
completed | March 23, 2026, 12:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0897b75e481909adc413fa73e9496 |
completed | March 23, 2026, 12:29 a.m. |
Created at: March 22, 2026, 3:48 p.m.