Triple
T8781076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Witte Corneliszoon de With |
E208726
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
de With
De With is a Dutch surname most notably associated with the 17th-century admiral Witte Corneliszoon de With of the Dutch Republic's navy.
|
E757974
|
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: de With | Statement: [Witte Corneliszoon de With, familyName, de With]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: de With Context triple: [Witte Corneliszoon de With, familyName, de With]
-
A.
De
De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
-
B.
deWilde
deWilde is a surname most notably associated with American child actor Brandon deWilde, known for his roles in classic mid-20th-century films.
-
C.
Dieze
The Dieze is a river in the southern Netherlands that flows through the city of ’s-Hertogenbosch and ultimately drains into the Dommel and Aa river system.
-
D.
Veeweyde
Veeweyde is a neighborhood-level district within the Brussels municipality of Anderlecht, known primarily as a residential area served by the Veeweyde metro station.
-
E.
DE-TH
DE-TH is the ISO 3166-2 subdivision code for the German federal state of Thuringia.
- 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: de With Triple: [Witte Corneliszoon de With, familyName, de With]
Generated description
De With is a Dutch surname most notably associated with the 17th-century admiral Witte Corneliszoon de With of the Dutch Republic's navy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: de With Target entity description: De With is a Dutch surname most notably associated with the 17th-century admiral Witte Corneliszoon de With of the Dutch Republic's navy.
-
A.
De
De is the given name of Zhu De, a prominent Chinese Communist military leader and one of the founders of the People’s Liberation Army.
-
B.
deWilde
deWilde is a surname most notably associated with American child actor Brandon deWilde, known for his roles in classic mid-20th-century films.
-
C.
Dieze
The Dieze is a river in the southern Netherlands that flows through the city of ’s-Hertogenbosch and ultimately drains into the Dommel and Aa river system.
-
D.
Veeweyde
Veeweyde is a neighborhood-level district within the Brussels municipality of Anderlecht, known primarily as a residential area served by the Veeweyde metro station.
-
E.
DE-TH
DE-TH is the ISO 3166-2 subdivision code for the German federal state of Thuringia.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f55b7b08190ab3e18cd634a144b |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51df4a608190883a093dbd169976 |
completed | April 3, 2026, 5:36 a.m. |
| NEDg | Description generation | batch_69cf54d366608190a94797b10389e6ca |
completed | April 3, 2026, 5:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf55940918819088ed8a6ea2f8f460 |
completed | April 3, 2026, 5:52 a.m. |
Created at: March 30, 2026, 6:42 p.m.