Triple
T14963044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EC4 |
E373113
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | EC4V |
E373113
|
NE FINISHED |
How this triple was built (2 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: EC4V | Statement: [EC4, hasSubdivision, EC4V]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EC4V Context triple: [EC4, hasSubdivision, EC4V]
-
A.
EC4N
EC4N is a central London postcode district covering part of the City of London, including areas around Bank and Monument.
-
B.
EC4
chosen
EC4 is a central London postcode district covering parts of the City of London, including key financial and commercial areas around Cannon Street and St Paul’s.
-
C.
EC1N
EC1N is a central London postcode district covering parts of the Holborn and Farringdon areas, known for its mix of legal, commercial, and residential properties.
-
D.
EC-M
EC-M is the vehicle registration and regional code assigned to the Macas area in Ecuador.
-
E.
EC75
The EC75 is an Airbus Helicopters medium twin-engine helicopter model, commonly known as the H175, used for roles such as offshore transport, search and rescue, and executive transport.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6d0487c8190b7754af8c5014b37 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969112d8819094e5d81a8ffa3b8a |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:40 a.m.