Triple
T6492865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thoiry |
E148083
|
entity |
| Predicate | hasBorderingCommune |
P28600
|
FINISHED |
| Object | Sergy |
E89751
|
NE FINISHED |
How this triple was built (2 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: Sergy | Statement: [Thoiry, hasBorderingCommune, Sergy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sergy Context triple: [Thoiry, hasBorderingCommune, Sergy]
-
A.
Sergy
chosen
Sergy is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
B.
Sergei
Sergei is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
C.
Vasilevsky
Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
-
D.
Vitaly
Vitaly is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
E.
Serge
Serge is a masculine given name of French origin, commonly used in Francophone countries and derived from the Latin name Sergius.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c009088f3081909cd467b05919de30 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06ab6abbc8190a4971ad5a654b0cd |
completed | March 22, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653bf5c30819083e4e5484b2bd8cc |
completed | March 27, 2026, 9:54 a.m. |
Created at: March 22, 2026, 4:53 p.m.