Triple
T22451524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IG postcode area |
E555001
|
entity |
| Predicate | containsPostcodeDistrict |
P32592
|
FINISHED |
| Object |
IG10
IG10 is a UK postal district covering Loughton and surrounding areas on the northeastern edge of Greater London and into Essex.
|
E1537118
|
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: IG10 | Statement: [IG postcode area, containsPostcodeDistrict, IG10]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IG10 Context triple: [IG postcode area, containsPostcodeDistrict, IG10]
-
A.
IGU
IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
-
B.
I10
I10 is the station code assigned to Shōji Station in Japan’s railway network.
-
C.
EGA I
EGA I is the first volume of the foundational algebraic geometry treatise "Éléments de Géométrie Algébrique" by Grothendieck and Dieudonné, introducing the basic language and concepts of schemes.
-
D.
IGR
IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
-
E.
IGRUA
IGRUA is a premier Indian government-run flying training institute that specializes in training commercial pilots and aviation professionals.
- 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: IG10 Triple: [IG postcode area, containsPostcodeDistrict, IG10]
Generated description
IG10 is a UK postal district covering Loughton and surrounding areas on the northeastern edge of Greater London and into Essex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: IG10 Target entity description: IG10 is a UK postal district covering Loughton and surrounding areas on the northeastern edge of Greater London and into Essex.
-
A.
IGU
IGU is the IATA airport code for Foz do Iguaçu International Airport in Brazil, serving the Iguaçu Falls region.
-
B.
I10
I10 is the station code assigned to Shōji Station in Japan’s railway network.
-
C.
EGA I
EGA I is the first volume of the foundational algebraic geometry treatise "Éléments de Géométrie Algébrique" by Grothendieck and Dieudonné, introducing the basic language and concepts of schemes.
-
D.
IGR
IGR is the IATA airport code for Cataratas del Iguazú International Airport serving Puerto Iguazú in Argentina, a gateway to the Iguazú Falls.
-
E.
IGRUA
IGRUA is a premier Indian government-run flying training institute that specializes in training commercial pilots and aviation professionals.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ba6a88190a0a79e2c20fa8c08 |
completed | April 29, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b0c7b12e0819088c16dfd70792eba |
completed | May 18, 2026, 12:56 p.m. |
| NEDg | Description generation | batch_6a0b0d7be4d8819080173d9e877d2565 |
completed | May 18, 2026, 1 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b0e07f40c81908163967a1dc19516 |
completed | May 18, 2026, 1:03 p.m. |
Created at: April 16, 2026, 8:48 p.m.