Triple
T15952067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PZB |
E386840
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
PZB 70
PZB 70 is a specific variant of the German train protection system used to monitor and control train speeds for safety on railway networks.
|
E1188254
|
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: PZB 70 | Statement: [PZB, hasVariant, PZB 70]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PZB 70 Context triple: [PZB, hasVariant, PZB 70]
-
A.
PZ-90
PZ-90 is a geodetic coordinate reference system used by the Russian GLONASS satellite navigation system to define positions on Earth.
-
B.
PB-39
PB-39 is the vehicle registration code assigned to motor vehicles registered in Barnala district in the Indian state of Punjab.
-
C.
PB-05
PB-05 is the regional vehicle registration code assigned to the Ferozepur district in the Indian state of Punjab.
-
D.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
E.
PZ
PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
- 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: PZB 70 Triple: [PZB, hasVariant, PZB 70]
Generated description
PZB 70 is a specific variant of the German train protection system used to monitor and control train speeds for safety on railway networks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PZB 70 Target entity description: PZB 70 is a specific variant of the German train protection system used to monitor and control train speeds for safety on railway networks.
-
A.
PZ-90
PZ-90 is a geodetic coordinate reference system used by the Russian GLONASS satellite navigation system to define positions on Earth.
-
B.
PB-39
PB-39 is the vehicle registration code assigned to motor vehicles registered in Barnala district in the Indian state of Punjab.
-
C.
PB-05
PB-05 is the regional vehicle registration code assigned to the Ferozepur district in the Indian state of Punjab.
-
D.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
E.
PZ
PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156f687dc81908d4afd43ac0b2c8e |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3c1b49c819087e5a088d41963ec |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc4ba0a988190b1d93ce6479bac88 |
completed | May 9, 2026, 11:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc5902904819097a2c5efbde55882 |
completed | May 9, 2026, 11:38 p.m. |
Created at: April 10, 2026, 4:53 a.m.