Triple
T17442472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierre/Siders railway station |
E424691
|
entity |
| Predicate | hasBilingualName |
P24120
|
FINISHED |
| Object |
Sierre/Siders
Sierre/Siders is a bilingual town in the canton of Valais, Switzerland, known for its French- and German-speaking communities and its location in the Rhône valley.
|
E1269078
|
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: Sierre/Siders | Statement: [Sierre/Siders railway station, hasBilingualName, Sierre/Siders]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sierre/Siders Context triple: [Sierre/Siders railway station, hasBilingualName, Sierre/Siders]
-
A.
Sievers
Sievers is a German-language surname borne by various notable individuals across fields such as science, sports, and the arts.
-
B.
Seiler
Seiler is a surname, likely of Germanic origin, that appears as a variant of the family name Siler.
-
C.
Sijmons
Sijmons is a surname variant of Simons, commonly found in Dutch-speaking regions.
-
D.
Sissons
Sissons is an English surname most notably associated with the late BBC and ITN newsreader Peter Sissons.
-
E.
Sillers
Sillers is a minor character in the play "Inherit the Wind," serving as a working-class townsman who reflects the everyday community’s perspective during the trial.
- 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: Sierre/Siders Triple: [Sierre/Siders railway station, hasBilingualName, Sierre/Siders]
Generated description
Sierre/Siders is a bilingual town in the canton of Valais, Switzerland, known for its French- and German-speaking communities and its location in the Rhône valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sierre/Siders Target entity description: Sierre/Siders is a bilingual town in the canton of Valais, Switzerland, known for its French- and German-speaking communities and its location in the Rhône valley.
-
A.
Sievers
Sievers is a German-language surname borne by various notable individuals across fields such as science, sports, and the arts.
-
B.
Seiler
Seiler is a surname, likely of Germanic origin, that appears as a variant of the family name Siler.
-
C.
Sijmons
Sijmons is a surname variant of Simons, commonly found in Dutch-speaking regions.
-
D.
Sissons
Sissons is an English surname most notably associated with the late BBC and ITN newsreader Peter Sissons.
-
E.
Sillers
Sillers is a minor character in the play "Inherit the Wind," serving as a working-class townsman who reflects the everyday community’s perspective during the trial.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff82bbc819095dd0621137da809 |
completed | April 19, 2026, 3:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01aff63d688190b8fa63c8edafc01c |
completed | May 11, 2026, 10:31 a.m. |
| NEDg | Description generation | batch_6a01b0a265348190a884a58f3caf54df |
completed | May 11, 2026, 10:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01b1b0553c8190bb76969fe95154ff |
completed | May 11, 2026, 10:38 a.m. |
Created at: April 10, 2026, 5:47 a.m.