Triple
T4538752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remagen |
E107474
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Kripp
Kripp is a district of the town of Remagen in the Rhineland-Palatinate region of Germany, situated along the Rhine River.
|
E450988
|
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: Kripp | Statement: [Remagen, hasSubdivision, Kripp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kripp Context triple: [Remagen, hasSubdivision, Kripp]
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Krolloper
Krolloper was a historic Berlin theater and opera house known for its innovative productions and its role as the meeting place of the Reichstag during the Weimar Republic.
-
C.
Daddy Day Care
Daddy Day Care is a 2003 family comedy film about two unemployed fathers who start an improvised daycare center, leading to chaotic and humorous situations.
-
D.
Kiddo
Kiddo is a music producer known for working on the track "Elevation."
-
E.
Lapsi
Lapsi is a traditional North Indian sweet dish made from broken wheat, ghee, and sugar, commonly prepared during festivals and special occasions in regions like Bundelkhand.
- 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: Kripp Triple: [Remagen, hasSubdivision, Kripp]
Generated description
Kripp is a district of the town of Remagen in the Rhineland-Palatinate region of Germany, situated along the Rhine River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kripp Target entity description: Kripp is a district of the town of Remagen in the Rhineland-Palatinate region of Germany, situated along the Rhine River.
-
A.
Kiddyland
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Krolloper
Krolloper was a historic Berlin theater and opera house known for its innovative productions and its role as the meeting place of the Reichstag during the Weimar Republic.
-
C.
Daddy Day Care
Daddy Day Care is a 2003 family comedy film about two unemployed fathers who start an improvised daycare center, leading to chaotic and humorous situations.
-
D.
Kiddo
Kiddo is a music producer known for working on the track "Elevation."
-
E.
Lapsi
Lapsi is a traditional North Indian sweet dish made from broken wheat, ghee, and sugar, commonly prepared during festivals and special occasions in regions like Bundelkhand.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57ba327c8190a7f12e14077b1fa7 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacfff41481908a5c97ab4fcb9259 |
completed | March 20, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69bdb32911cc8190a8624d54dad6355e |
completed | March 20, 2026, 8:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdb3a0bf908190b9a029f47e6be941 |
completed | March 20, 2026, 8:52 p.m. |
Created at: March 20, 2026, 1:04 p.m.