Triple
T15586484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prinzregentenplatz U-Bahn station |
E374633
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
PZ
PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
|
E1165772
|
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: PZ | Statement: [Prinzregentenplatz U-Bahn station, hasStationCode, PZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PZ Context triple: [Prinzregentenplatz U-Bahn station, hasStationCode, PZ]
-
A.
PZ
PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
-
B.
PZ
PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
-
C.
PZ
PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
-
D.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
E.
ZP
ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
- 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: PZ Triple: [Prinzregentenplatz U-Bahn station, hasStationCode, PZ]
Generated description
PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PZ Target entity description: PZ is the station code for Prinzregentenplatz, a Munich U-Bahn station on the city’s rapid transit network.
-
A.
PZ
PZ is the vehicle registration code used on license plates for vehicles registered in the Preveza regional unit of Greece.
-
B.
PZ
PZ is the IATA airline designator assigned to LATAM Airlines Paraguay, the Paraguayan branch of the LATAM Airlines Group.
-
C.
PZ
PZ is the Italian vehicle registration code assigned to the Province of Potenza in the Basilicata region.
-
D.
PZ
PZ is the commonly used abbreviation for Peshawar Zalmi, a professional cricket franchise that competes in the Pakistan Super League.
-
E.
ZP
ZP is a German vehicle registration code assigned to the Erzgebirgskreis district in the state of Saxony.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e4900408190aadb48b001db4169 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c5166d88190ab14c7779e3e8e1f |
completed | May 9, 2026, 3:01 p.m. |
| NEDg | Description generation | batch_69ff50183f608190811cbff769cdd110 |
completed | May 9, 2026, 3:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff52eedbc08190be2f62326b00c8c7 |
completed | May 9, 2026, 3:29 p.m. |
Created at: April 10, 2026, 4:11 a.m.