Triple
T8796299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nossa Senhora da Paz metro station |
E209296
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
NPZ
NPZ is the station code for Nossa Senhora da Paz, a metro station in Rio de Janeiro, Brazil.
|
E759570
|
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: NPZ | Statement: [Nossa Senhora da Paz metro station, hasStationCode, NPZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NPZ Context triple: [Nossa Senhora da Paz metro station, hasStationCode, NPZ]
-
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.
NPAZ
NPAZ is the acronym for Zimbabwe’s National Prosecuting Authority, the state body responsible for directing public prosecutions and upholding criminal justice in the country.
-
D.
NZPM
NZPM is the ICAO airport code for Palmerston North Airport in Palmerston North, New Zealand.
-
E.
.np
.np is the country code top-level domain (ccTLD) assigned to Nepal for use in internet addresses.
- 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: NPZ Triple: [Nossa Senhora da Paz metro station, hasStationCode, NPZ]
Generated description
NPZ is the station code for Nossa Senhora da Paz, a metro station in Rio de Janeiro, Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NPZ Target entity description: NPZ is the station code for Nossa Senhora da Paz, a metro station in Rio de Janeiro, Brazil.
-
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.
NPAZ
NPAZ is the acronym for Zimbabwe’s National Prosecuting Authority, the state body responsible for directing public prosecutions and upholding criminal justice in the country.
-
D.
NZPM
NZPM is the ICAO airport code for Palmerston North Airport in Palmerston North, New Zealand.
-
E.
.np
.np is the country code top-level domain (ccTLD) assigned to Nepal for use in internet addresses.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa24ca08190a7738a7f1c446456 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f5d655881909013ac3e2ac0cebb |
completed | April 3, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69cf71c118848190a937ecf714556ef3 |
completed | April 3, 2026, 7:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf744b17e88190b14607e6dff823a3 |
completed | April 3, 2026, 8:03 a.m. |
Created at: March 30, 2026, 6:44 p.m.