Triple
T1195321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Willem Daendels |
E25655
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Hattem |
E114099
|
NE FINISHED |
How this triple was built (2 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: Hattem | Statement: [Herman Willem Daendels, placeOfBirth, Hattem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hattem Context triple: [Herman Willem Daendels, placeOfBirth, Hattem]
-
A.
Hampoort
Hampoort is a historic city gate, likely part of the old fortifications of a European town or city.
-
B.
Bornheim
Bornheim is a lively residential and nightlife district in Frankfurt am Main, Germany, known for its traditional cider taverns, historic streets, and vibrant local culture.
-
C.
Bredevoort
chosen
Bredevoort is a small historic town in the Dutch province of Gelderland, known for its well-preserved medieval character and its reputation as a national "book town."
-
D.
Shingletown
Shingletown is a small rural community in Northern California known for its forested setting near Lassen Volcanic National Park.
-
E.
Harrold
Harrold is a given name and surname, used as a variant spelling of Harold.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd78f61c8190bdba2255d35a8fe4 |
completed | March 1, 2026, 10:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac7650de3c8190b2c246436a3d25b1 |
completed | March 7, 2026, 7:02 p.m. |
Created at: March 1, 2026, 7:46 p.m.