Triple
T21170189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Margarets railway station |
E521669
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
SMG
SMG is the National Rail station code for St Margarets railway station in London, England.
|
E1470338
|
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: SMG | Statement: [St Margarets railway station, hasStationCode, SMG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SMG Context triple: [St Margarets railway station, hasStationCode, SMG]
-
A.
SMG
SMG is a private company specializing in the management and operation of public assembly facilities such as stadiums, arenas, and convention centers.
-
B.
SMG
SMG is the commonly used abbreviation for Sai Masu Gida, a nickname associated with Nigerian football club Kano Pillars FC.
-
C.
SMG
SMG is the abbreviation for the Science Museum Group, a UK-based organization that manages several major science and technology museums.
-
D.
SMG World
SMG World is a global venue management company that operates and manages convention centers, stadiums, arenas, and other large public facilities.
-
E.
CMG
CMG is China’s state-owned national media conglomerate that oversees major television, radio, and online broadcasting services.
- 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: SMG Triple: [St Margarets railway station, hasStationCode, SMG]
Generated description
SMG is the National Rail station code for St Margarets railway station in London, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SMG Target entity description: SMG is the National Rail station code for St Margarets railway station in London, England.
-
A.
SMG
SMG is the abbreviation for the Science Museum Group, a UK-based organization that manages several major science and technology museums.
-
B.
SMG
SMG is a private company specializing in the management and operation of public assembly facilities such as stadiums, arenas, and convention centers.
-
C.
SMG
SMG is the commonly used abbreviation for Sai Masu Gida, a nickname associated with Nigerian football club Kano Pillars FC.
-
D.
SMG World
SMG World is a global venue management company that operates and manages convention centers, stadiums, arenas, and other large public facilities.
-
E.
CMG
CMG is China’s state-owned national media conglomerate that oversees major television, radio, and online broadcasting services.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72712893081908e394ccc7e0cbb53 |
completed | April 21, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a097573a08481909695019432940d39 |
completed | May 17, 2026, 7:59 a.m. |
| NEDg | Description generation | batch_6a09764338fc8190be908a6fa9457d18 |
completed | May 17, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0978016f188190b8e2d2c7b1b01977 |
completed | May 17, 2026, 8:10 a.m. |
Created at: April 16, 2026, 3 p.m.