Triple
T12990087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senegal national football team |
E321880
|
entity |
| Predicate | fifaTrigramme |
P6278
|
FINISHED |
| Object |
SEN
SEN is the official FIFA trigramme used to represent the Senegal national football team in international competitions and records.
|
E1014586
|
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: SEN | Statement: [Senegal national football team, fifaTrigramme, SEN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SEN Context triple: [Senegal national football team, fifaTrigramme, SEN]
-
A.
SEN
SEN is the National Rail station code for Shenstone railway station in Staffordshire, England.
-
B.
SEN
SEN is the three-letter IATA airport code for London Southend Airport in the United Kingdom.
-
C.
SEL
SEL is the former IATA airport code that once designated Seoul’s main international airport before it was replaced by newer facilities.
-
D.
ENS
ENS is a common abbreviation for the École Normale Supérieure, a prestigious French grande école known for its elite training in the sciences and humanities.
-
E.
SED
SED was the ruling Marxist–Leninist party that governed East Germany (the German Democratic Republic) from its founding in 1949 until the end of communist rule in 1989.
- 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: SEN Triple: [Senegal national football team, fifaTrigramme, SEN]
Generated description
SEN is the official FIFA trigramme used to represent the Senegal national football team in international competitions and records.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SEN Target entity description: SEN is the official FIFA trigramme used to represent the Senegal national football team in international competitions and records.
-
A.
SEN
SEN is the three-letter IATA airport code for London Southend Airport in the United Kingdom.
-
B.
SEN
SEN is the National Rail station code for Shenstone railway station in Staffordshire, England.
-
C.
SEL
SEL is the former IATA airport code that once designated Seoul’s main international airport before it was replaced by newer facilities.
-
D.
ENS
ENS is a common abbreviation for the École Normale Supérieure, a prestigious French grande école known for its elite training in the sciences and humanities.
-
E.
SED
SED was the ruling Marxist–Leninist party that governed East Germany (the German Democratic Republic) from its founding in 1949 until the end of communist rule in 1989.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e75b9f88190a54372c2a1223a4e |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8f942588190b69a3067d5145182 |
completed | May 3, 2026, 2:54 a.m. |
| NEDg | Description generation | batch_69f6b9dcd5cc8190bff5bd153c007866 |
completed | May 3, 2026, 2:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6bb304f7c8190a02aa2c5f71cea89 |
completed | May 3, 2026, 3:04 a.m. |
Created at: April 9, 2026, 8:43 p.m.