Triple
T14731880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wollongong railway station |
E346094
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
WOL
WOL is the station code for Wollongong railway station in New South Wales, Australia.
|
E1117900
|
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: WOL | Statement: [Wollongong railway station, hasStationCode, WOL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WOL Context triple: [Wollongong railway station, hasStationCode, WOL]
-
A.
WOL
WOL is a German vehicle registration code formerly used for the town of Wolfach in the Ortenaukreis district of Baden-Württemberg.
-
B.
wol
"wol" is the ISO 639-3 language code for Wolof, a major Atlantic language spoken primarily in Senegal, The Gambia, and Mauritania.
-
C.
WOFL
WOFL is a Fox-affiliated television station serving the Orlando, Florida media market.
-
D.
WoS
WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
-
E.
WLO
WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
- 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: WOL Triple: [Wollongong railway station, hasStationCode, WOL]
Generated description
WOL is the station code for Wollongong railway station in New South Wales, Australia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: WOL Target entity description: WOL is the station code for Wollongong railway station in New South Wales, Australia.
-
A.
WOL
WOL is a German vehicle registration code formerly used for the town of Wolfach in the Ortenaukreis district of Baden-Württemberg.
-
B.
wol
"wol" is the ISO 639-3 language code for Wolof, a major Atlantic language spoken primarily in Senegal, The Gambia, and Mauritania.
-
C.
WOFL
WOFL is a Fox-affiliated television station serving the Orlando, Florida media market.
-
D.
WoS
WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
-
E.
WLO
WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec26311c8819093a81ff0fa43b33b |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb89ea388190b356df74e36023f7 |
completed | May 8, 2026, 3:04 p.m. |
| NEDg | Description generation | batch_69fdfdd73dcc8190bd0340b2f2a2c54a |
completed | May 8, 2026, 3:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdfe70e03481909eb9a9bf863f826b |
completed | May 8, 2026, 3:17 p.m. |
Created at: April 10, 2026, 1:29 a.m.