Triple
T1983339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Étienne |
E43079
|
entity |
| Predicate | hasRiver |
P165
|
FINISHED |
| Object |
Furan
Furan is a river in central France that flows through the city of Saint-Étienne before joining the Loire.
|
E221328
|
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: Furan | Statement: [Saint-Étienne, hasRiver, Furan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Furan Context triple: [Saint-Étienne, hasRiver, Furan]
-
A.
Corachol
Corachol is a subfamily of Uto-Aztecan languages that includes closely related indigenous languages spoken in western Mexico.
-
B.
THF
THF is the former Berlin Tempelhof Airport, a historically significant airfield known for its role in the Berlin Airlift and its later conversion into a vast urban park.
-
C.
Fremulon
Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
-
D.
Feigl
Feigl is a German-language surname borne by various notable individuals, including philosophers, scientists, and artists.
-
E.
Tykocin
Tykocin is a historic town in northeastern Poland known for its well-preserved Jewish heritage, baroque architecture, and role in Polish royal and noble history.
- 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: Furan Triple: [Saint-Étienne, hasRiver, Furan]
Generated description
Furan is a river in central France that flows through the city of Saint-Étienne before joining the Loire.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Furan Target entity description: Furan is a river in central France that flows through the city of Saint-Étienne before joining the Loire.
-
A.
Corachol
Corachol is a subfamily of Uto-Aztecan languages that includes closely related indigenous languages spoken in western Mexico.
-
B.
THF
THF is the former Berlin Tempelhof Airport, a historically significant airfield known for its role in the Berlin Airlift and its later conversion into a vast urban park.
-
C.
Fremulon
Fremulon is a television production company founded by Michael Schur, best known for producing acclaimed comedy series such as Brooklyn Nine-Nine.
-
D.
Feigl
Feigl is a German-language surname borne by various notable individuals, including philosophers, scientists, and artists.
-
E.
Tykocin
Tykocin is a historic town in northeastern Poland known for its well-preserved Jewish heritage, baroque architecture, and role in Polish royal and noble history.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb820815481908aac6d89b437225b |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae032e1f648190acb502b9f82fe8c2 |
completed | March 8, 2026, 11:15 p.m. |
| NEDg | Description generation | batch_69ae03b52ed08190a8c8fb8f81073bb3 |
completed | March 8, 2026, 11:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae0433b90c81909af348d9a3dcdbec |
completed | March 8, 2026, 11:20 p.m. |
Created at: March 4, 2026, 7:37 p.m.