Triple
T20719129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ancre River |
E509261
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object |
Englebelmer
Englebelmer is a small commune in the Somme department of northern France, situated in the historical Picardy region.
|
E1447692
|
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: Englebelmer | Statement: [Ancre River, flowsThrough, Englebelmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Englebelmer Context triple: [Ancre River, flowsThrough, Englebelmer]
-
A.
Schermerhorne
Schermerhorne is a variant spelling of the Dutch surname Schermerhorn, which is associated with a historic family name and several notable places and individuals.
-
B.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
C.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
D.
Marheineke
Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
-
E.
Kellinghausen
Kellinghausen is a locality within the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
- 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: Englebelmer Triple: [Ancre River, flowsThrough, Englebelmer]
Generated description
Englebelmer is a small commune in the Somme department of northern France, situated in the historical Picardy region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Englebelmer Target entity description: Englebelmer is a small commune in the Somme department of northern France, situated in the historical Picardy region.
-
A.
Schermerhorne
Schermerhorne is a variant spelling of the Dutch surname Schermerhorn, which is associated with a historic family name and several notable places and individuals.
-
B.
Hagenborgh
Hagenborgh is a notable landmark building in the Dutch city of Almelo, recognized for its prominent role in the local urban landscape.
-
C.
Belpberg
Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
-
D.
Marheineke
Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
-
E.
Kellinghausen
Kellinghausen is a locality within the town of Rüthen in the district of Soest, North Rhine-Westphalia, Germany.
- 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1d39bec8190b3642b0d6d833375 |
completed | April 21, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08e0552fe88190aa5557fa83b7ed40 |
completed | May 16, 2026, 9:23 p.m. |
| NEDg | Description generation | batch_6a08e4808ac881908d527d462833ba84 |
completed | May 16, 2026, 9:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08e4eccb0881908e536964d86650d1 |
completed | May 16, 2026, 9:43 p.m. |
Created at: April 16, 2026, 12:26 p.m.