Triple
T9248949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watford North railway station |
E222269
|
entity |
| Predicate | stationCode |
P1289
|
FINISHED |
| Object |
WFN
WFN is the three-letter National Rail station code assigned to Watford North railway station in Hertfordshire, England.
|
E786544
|
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: WFN | Statement: [Watford North railway station, stationCode, WFN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WFN Context triple: [Watford North railway station, stationCode, WFN]
-
A.
FWN
FWN is the standard abbreviation used for the Fort Wayne TinCaps, a Minor League Baseball team based in Fort Wayne, Indiana.
-
B.
WFJ
WFJ is the National Rail station code for Watford Junction, a major railway hub in Hertfordshire, England, serving commuter, regional, and long-distance services.
-
C.
WFM (former)
WFM (former) was the stock ticker symbol under which Whole Foods Market was publicly traded before its acquisition by Amazon.
-
D.
WFA
WFA is the abbreviation for The Women's Football Association, the former governing body for women's football in England.
-
E.
WF
WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
- 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: WFN Triple: [Watford North railway station, stationCode, WFN]
Generated description
WFN is the three-letter National Rail station code assigned to Watford North railway station in Hertfordshire, England.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WFN Target entity description: WFN is the three-letter National Rail station code assigned to Watford North railway station in Hertfordshire, England.
-
A.
FWN
FWN is the standard abbreviation used for the Fort Wayne TinCaps, a Minor League Baseball team based in Fort Wayne, Indiana.
-
B.
WFJ
WFJ is the National Rail station code for Watford Junction, a major railway hub in Hertfordshire, England, serving commuter, regional, and long-distance services.
-
C.
WFM (former)
WFM (former) was the stock ticker symbol under which Whole Foods Market was publicly traded before its acquisition by Amazon.
-
D.
WFA
WFA is the abbreviation for The Women's Football Association, the former governing body for women's football in England.
-
E.
WF
WF is the common abbreviation for Wikifunctions, a Wikimedia project aimed at creating a collaborative catalog of reusable functions.
- 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_69ca841d2b18819089f9faf5b2c2aec0 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd05f6d62c8190a1e33f1854767b47 |
completed | April 1, 2026, 11:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077fed7888190a5d36bc2ee4c2bd2 |
completed | April 4, 2026, 2:31 a.m. |
| NEDg | Description generation | batch_69d0787b68ac819094acdec0ad7462ac |
completed | April 4, 2026, 2:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d07900c7588190869c26dc76fe97e7 |
completed | April 4, 2026, 2:35 a.m. |
Created at: March 30, 2026, 7:31 p.m.