Triple
T4045270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germanisches Nationalmuseum |
E84049
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
GNM
GNM is the abbreviation for the Germanisches Nationalmuseum, a major museum in Nuremberg dedicated to German art and cultural history.
|
E408443
|
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: GNM | Statement: [Germanisches Nationalmuseum, shortName, GNM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GNM Context triple: [Germanisches Nationalmuseum, shortName, GNM]
-
A.
EGNM
EGNM is the ICAO airport code for Leeds Bradford Airport, a regional international airport serving the cities of Leeds and Bradford in West Yorkshire, England.
-
B.
GN
GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
-
C.
GNB
GNB is the commonly used abbreviation for the Good News Bible, a modern English translation of the Christian Bible known for its clear and simple language.
-
D.
GNB
GNB is the three-letter ISO 3166-1 alpha-3 country code assigned to Guinea-Bissau.
-
E.
MGN
MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
- 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: GNM Triple: [Germanisches Nationalmuseum, shortName, GNM]
Generated description
GNM is the abbreviation for the Germanisches Nationalmuseum, a major museum in Nuremberg dedicated to German art and cultural history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: GNM Target entity description: GNM is the abbreviation for the Germanisches Nationalmuseum, a major museum in Nuremberg dedicated to German art and cultural history.
-
A.
EGNM
EGNM is the ICAO airport code for Leeds Bradford Airport, a regional international airport serving the cities of Leeds and Bradford in West Yorkshire, England.
-
B.
GN
GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
-
C.
GNB
GNB is the commonly used abbreviation for the Good News Bible, a modern English translation of the Christian Bible known for its clear and simple language.
-
D.
GNB
GNB is the three-letter ISO 3166-1 alpha-3 country code assigned to Guinea-Bissau.
-
E.
MGN
MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5f85d48190ba80a0a24fbe438a |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b55652228c8190a9f301676deb0055 |
completed | March 14, 2026, 12:36 p.m. |
| NEDg | Description generation | batch_69b556fec4708190b221893ec35f1a38 |
completed | March 14, 2026, 12:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b557f73cbc8190b904089ab0fa97d6 |
completed | March 14, 2026, 12:43 p.m. |
Created at: March 9, 2026, 3:37 p.m.