Triple
T749550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidelberg |
E15415
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
HD
HD is the vehicle registration code used for the German city of Heidelberg.
|
E89010
|
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: HD | Statement: [Heidelberg, hasVehicleRegistrationCode, HD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HD Context triple: [Heidelberg, hasVehicleRegistrationCode, HD]
-
A.
HD
HD is the New York Stock Exchange ticker symbol for The Home Depot, the largest home improvement retail chain in the United States.
-
B.
H.264
H.264 is a widely used video compression standard known for delivering high-quality video at relatively low bitrates, commonly employed in streaming, broadcasting, and video recording.
-
C.
ProRes
ProRes is a high-quality, high-performance video compression format developed by Apple and widely used in professional video production and post‑production workflows.
-
D.
HDI
The HDI is a composite statistic used by the United Nations to measure and compare countries’ overall human development based on health, education, and standard of living.
-
E.
Dolby Vision
Dolby Vision is a high-dynamic-range (HDR) imaging technology that enhances video with greater brightness, contrast, and color accuracy for a more lifelike viewing experience.
- 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: HD Triple: [Heidelberg, hasVehicleRegistrationCode, HD]
Generated description
HD is the vehicle registration code used for the German city of Heidelberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HD Target entity description: HD is the vehicle registration code used for the German city of Heidelberg.
-
A.
HD
HD is the New York Stock Exchange ticker symbol for The Home Depot, the largest home improvement retail chain in the United States.
-
B.
H.264
H.264 is a widely used video compression standard known for delivering high-quality video at relatively low bitrates, commonly employed in streaming, broadcasting, and video recording.
-
C.
ProRes
ProRes is a high-quality, high-performance video compression format developed by Apple and widely used in professional video production and post‑production workflows.
-
D.
HDI
The HDI is a composite statistic used by the United Nations to measure and compare countries’ overall human development based on health, education, and standard of living.
-
E.
Dolby Vision
Dolby Vision is a high-dynamic-range (HDR) imaging technology that enhances video with greater brightness, contrast, and color accuracy for a more lifelike viewing experience.
- 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_69a493599a0081908da65f3407af1ef2 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a6304e0c8190827fb57c5cac2da9 |
completed | March 1, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a654e8d80481908505896fb6ead36b |
completed | March 3, 2026, 3:26 a.m. |
| NEDg | Description generation | batch_69a655c79044819098e36081b754c9be |
completed | March 3, 2026, 3:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a65638cd5881908b421d9d8a90291b |
completed | March 3, 2026, 3:32 a.m. |
Created at: March 1, 2026, 7:37 p.m.