Triple
T14070189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neeltgen Willemsdr. van Zuytbrouck |
E338585
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object |
Neeltgen
Neeltgen is a historical Dutch woman whose full name is Neeltgen Willemsdr. van Zuytbrouck.
|
E1078081
|
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: Neeltgen | Statement: [Neeltgen Willemsdr. van Zuytbrouck, hasGivenName, Neeltgen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neeltgen Context triple: [Neeltgen Willemsdr. van Zuytbrouck, hasGivenName, Neeltgen]
-
A.
Neeleman
Neeleman is a surname most notably associated with David Neeleman, the Brazilian-American entrepreneur and founder of multiple airlines including JetBlue Airways.
-
B.
Danneels
Danneels is a Belgian surname most notably associated with Cardinal Godfried Danneels, a prominent Roman Catholic prelate and former Archbishop of Mechelen-Brussels.
-
C.
Goeneutte
Goeneutte is the surname of Norbert Goeneutte, a French painter and printmaker associated with the Impressionist movement.
-
D.
Marloes
Marloes is a coastal village in Pembrokeshire, Wales, known for its dramatic cliffs, nearby islands rich in wildlife, and scenic seaside landscapes.
-
E.
Nele
Nele is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its philosophical depth and exploration of human values.
- 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: Neeltgen Triple: [Neeltgen Willemsdr. van Zuytbrouck, hasGivenName, Neeltgen]
Generated description
Neeltgen is a historical Dutch woman whose full name is Neeltgen Willemsdr. van Zuytbrouck.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Neeltgen Target entity description: Neeltgen is a historical Dutch woman whose full name is Neeltgen Willemsdr. van Zuytbrouck.
-
A.
Neeleman
Neeleman is a surname most notably associated with David Neeleman, the Brazilian-American entrepreneur and founder of multiple airlines including JetBlue Airways.
-
B.
Danneels
Danneels is a Belgian surname most notably associated with Cardinal Godfried Danneels, a prominent Roman Catholic prelate and former Archbishop of Mechelen-Brussels.
-
C.
Goeneutte
Goeneutte is the surname of Norbert Goeneutte, a French painter and printmaker associated with the Impressionist movement.
-
D.
Marloes
Marloes is a coastal village in Pembrokeshire, Wales, known for its dramatic cliffs, nearby islands rich in wildlife, and scenic seaside landscapes.
-
E.
Nele
Nele is a Kannada novel by acclaimed Indian writer S. L. Bhyrappa, known for its philosophical depth and exploration of human values.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568d0404819087e0fe37c72162cb |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb66cfe2c8190af8354316d4f4df9 |
completed | May 7, 2026, 3:57 p.m. |
| NEDg | Description generation | batch_69fcc5c893dc81908538136e0f9170ca |
completed | May 7, 2026, 5:03 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fcc64ac93c8190ad40a04c74f70e18 |
completed | May 7, 2026, 5:05 p.m. |
Created at: April 9, 2026, 10:21 p.m.