Triple
T14197216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nuneaton railway station |
E351867
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
NUN
NUN is the National Rail station code for Nuneaton railway station in Warwickshire, England.
|
E1084973
|
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: NUN | Statement: [Nuneaton railway station, hasStationCode, NUN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NUN Context triple: [Nuneaton railway station, hasStationCode, NUN]
-
A.
NUN
NUN is the IATA airport code for Saufley Field, a military airfield near Pensacola, Florida.
-
B.
Nun
Nun is the primordial watery chaos in ancient Egyptian mythology, representing the formless abyss from which creation first emerged.
-
C.
Nu
Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
-
D.
NUE
NUE is the three-letter IATA airport code for Nuremberg Airport in Nuremberg, Germany.
-
E.
NNU
NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
- 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: NUN Triple: [Nuneaton railway station, hasStationCode, NUN]
Generated description
NUN is the National Rail station code for Nuneaton railway station in Warwickshire, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NUN Target entity description: NUN is the National Rail station code for Nuneaton railway station in Warwickshire, England.
-
A.
NUN
NUN is the IATA airport code for Saufley Field, a military airfield near Pensacola, Florida.
-
B.
Nun
Nun is the primordial watery chaos in ancient Egyptian mythology, representing the formless abyss from which creation first emerged.
-
C.
Nu
Nu is the given name of U Nu, the first Prime Minister of independent Burma (now Myanmar) and a prominent mid-20th-century political leader.
-
D.
NUE
NUE is the three-letter IATA airport code for Nuremberg Airport in Nuremberg, Germany.
-
E.
NNU
NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61e30f208190b61c1c7bd3501156 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd194d14008190a74021ff5a3e51d1 |
completed | May 7, 2026, 10:59 p.m. |
| NEDg | Description generation | batch_69fd1ab3f83881908113259c23fe1028 |
completed | May 7, 2026, 11:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd1b87a0c48190a68367525ed9d2cb |
completed | May 7, 2026, 11:08 p.m. |
Created at: April 10, 2026, 1:04 a.m.