Triple
T9553645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regensburg (district) |
E230485
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Laber
Laber is a river in Bavaria, Germany, that flows through the Regensburg district.
|
E807347
|
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: Laber | Statement: [Regensburg (district), hasRiver, Laber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laber Context triple: [Regensburg (district), hasRiver, Laber]
-
A.
Labori
Labori was a prominent French defense lawyer best known for representing Alfred Dreyfus during the politically charged Dreyfus affair.
-
B.
Labo
Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
-
C.
Laborec
Laborec is a river in eastern Slovakia that flows through the Carpathian region and is a tributary of the Latorica River.
-
D.
The Grinder
The Grinder is an American television sitcom that satirizes legal dramas, starring Rob Lowe and Fred Savage as brothers whose lives are upended when a TV lawyer returns home believing he can practice real law.
-
E.
The Lab
The Lab is a South African television drama series centered on the high-stakes world of corporate finance and investment banking.
- 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: Laber Triple: [Regensburg (district), hasRiver, Laber]
Generated description
Laber is a river in Bavaria, Germany, that flows through the Regensburg district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Laber Target entity description: Laber is a river in Bavaria, Germany, that flows through the Regensburg district.
-
A.
Labori
Labori was a prominent French defense lawyer best known for representing Alfred Dreyfus during the politically charged Dreyfus affair.
-
B.
Labo
Labo is a municipality in the Philippine province of Camarines Norte known for its agricultural economy and natural attractions such as caves, waterfalls, and mineral resources.
-
C.
Laborec
Laborec is a river in eastern Slovakia that flows through the Carpathian region and is a tributary of the Latorica River.
-
D.
The Grinder
The Grinder is an American television sitcom that satirizes legal dramas, starring Rob Lowe and Fred Savage as brothers whose lives are upended when a TV lawyer returns home believing he can practice real law.
-
E.
The Lab
The Lab is a South African television drama series centered on the high-stakes world of corporate finance and investment banking.
- 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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99217de48190b528e14fd02ee987 |
completed | April 1, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1528bd99881909e3f51472a99917f |
completed | April 4, 2026, 6:03 p.m. |
| NEDg | Description generation | batch_69d156a5b65c8190a7c7616b6df6c181 |
completed | April 4, 2026, 6:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d15740036c8190ada8ccf59c1436d9 |
completed | April 4, 2026, 6:24 p.m. |
Created at: March 30, 2026, 8:02 p.m.