Triple
T15811873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weston Milton railway station |
E383373
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
WNM
WNM is the National Rail station code for Weston Milton railway station in Weston-super-Mare, England.
|
E1177839
|
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: WNM | Statement: [Weston Milton railway station, hasStationCode, WNM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WNM Context triple: [Weston Milton railway station, hasStationCode, WNM]
-
A.
WMN
WMN is the National Rail station code for Warminster railway station in Wiltshire, England.
-
B.
WNA
WNA is the acronym for the World Nuclear Association, an international organization that promotes the peaceful use and development of nuclear power worldwide.
-
C.
WNL
WNL is the National Rail station code for Whinhill railway station in Inverclyde, Scotland.
-
D.
WN
WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
-
E.
WN
WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
- 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: WNM Triple: [Weston Milton railway station, hasStationCode, WNM]
Generated description
WNM is the National Rail station code for Weston Milton railway station in Weston-super-Mare, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WNM Target entity description: WNM is the National Rail station code for Weston Milton railway station in Weston-super-Mare, England.
-
A.
WMN
WMN is the National Rail station code for Warminster railway station in Wiltshire, England.
-
B.
WNA
WNA is the acronym for the World Nuclear Association, an international organization that promotes the peaceful use and development of nuclear power worldwide.
-
C.
WNL
WNL is the National Rail station code for Whinhill railway station in Inverclyde, Scotland.
-
D.
WN
WN is the vehicle registration code used on license plates for the Waiblingen district in the German state of Baden-Württemberg.
-
E.
WN
WN is the IATA airline designator used to identify Southwest Airlines in flight schedules, ticketing, and aviation operations.
- 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_69d86da2858c819090cc8481e7207b6e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b52bbb888190b226567e84ced7e9 |
completed | April 16, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff9993c86c8190b1d106af7537080a |
completed | May 9, 2026, 8:31 p.m. |
| NEDg | Description generation | batch_69ff9a32d6bc81909d8023de562a2517 |
completed | May 9, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff9adb25448190b805046ae6c3ee17 |
completed | May 9, 2026, 8:36 p.m. |
Created at: April 10, 2026, 4:49 a.m.