Triple
T13905721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazel Grove railway station |
E334343
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
HAZ
HAZ is the National Rail station code for Hazel Grove railway station in Greater Manchester, England.
|
E1067687
|
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: HAZ | Statement: [Hazel Grove railway station, hasStationCode, HAZ]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HAZ Context triple: [Hazel Grove railway station, hasStationCode, HAZ]
-
A.
HAJ
HAJ is the three-letter IATA airport code for Hannover Airport in Hanover, Germany.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
HEAZ
HEAZ is the ICAO airport code for Almaza Airport, a military and general aviation airfield serving Cairo, Egypt.
-
D.
Hazard
Hazard is the middle name of Oliver Hazard Perry, the famed U.S. naval commander known for his victory in the Battle of Lake Erie during the War of 1812.
-
E.
HAF
HAF is the commonly used abbreviation for the Hellenic Air Force, the air warfare branch of Greece’s armed forces.
- 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: HAZ Triple: [Hazel Grove railway station, hasStationCode, HAZ]
Generated description
HAZ is the National Rail station code for Hazel Grove railway station in Greater Manchester, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HAZ Target entity description: HAZ is the National Rail station code for Hazel Grove railway station in Greater Manchester, England.
-
A.
HAJ
HAJ is the three-letter IATA airport code for Hannover Airport in Hanover, Germany.
-
B.
HAV
HAV is the IATA airport code for José Martí International Airport, the main international gateway serving Havana, Cuba.
-
C.
HEAZ
HEAZ is the ICAO airport code for Almaza Airport, a military and general aviation airfield serving Cairo, Egypt.
-
D.
Hazard
Hazard is the middle name of Oliver Hazard Perry, the famed U.S. naval commander known for his victory in the Battle of Lake Erie during the War of 1812.
-
E.
HAF
HAF is the commonly used abbreviation for the Hellenic Air Force, the air warfare branch of Greece’s armed forces.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25dc26cc8190a7909980b1d34933 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c724c6188190ae0c2784c3b48a12 |
completed | May 3, 2026, 10:07 p.m. |
| NEDg | Description generation | batch_69f7c7e1247481908073c1e282c3619f |
completed | May 3, 2026, 10:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c8f2b5588190b6143d676eb648a0 |
completed | May 3, 2026, 10:15 p.m. |
Created at: April 9, 2026, 10:16 p.m.