Triple
T14731840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurstville railway station |
E346093
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
HUR
HUR is the station code used to identify Hurstville railway station in the Sydney Trains network.
|
E1117898
|
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: HUR | Statement: [Hurstville railway station, hasStationCode, HUR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HUR Context triple: [Hurstville railway station, hasStationCode, HUR]
-
A.
HURI
HURI is a Harvard University research institute dedicated to the interdisciplinary study of Ukrainian history, culture, language, and politics.
-
B.
HOR
HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
-
C.
HOR
HOR is the National Rail station code for Horley railway station in Surrey, England.
-
D.
Hur
Hur is a biblical figure from the Old Testament, traditionally regarded as a leader of Israel and associate of Moses during the Exodus.
-
E.
Hu
Hu is a common Chinese surname borne by many notable figures, including former Chinese president Hu Jintao.
- 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: HUR Triple: [Hurstville railway station, hasStationCode, HUR]
Generated description
HUR is the station code used to identify Hurstville railway station in the Sydney Trains network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HUR Target entity description: HUR is the station code used to identify Hurstville railway station in the Sydney Trains network.
-
A.
HURI
HURI is a Harvard University research institute dedicated to the interdisciplinary study of Ukrainian history, culture, language, and politics.
-
B.
HOR
HOR is the IATA airport code for Horta Airport, which serves the island of Faial in Portugal’s Azores archipelago.
-
C.
HOR
HOR is the National Rail station code for Horley railway station in Surrey, England.
-
D.
Hur
Hur is a biblical figure from the Old Testament, traditionally regarded as a leader of Israel and associate of Moses during the Exodus.
-
E.
Hu
Hu is a common Chinese surname borne by many notable figures, including former Chinese president Hu Jintao.
- 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.