Triple
T5331481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hector Lefuel |
E123318
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Lefuel |
E123318
|
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: Lefuel | Statement: [Hector Lefuel, hasSurname, Lefuel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lefuel Context triple: [Hector Lefuel, hasSurname, Lefuel]
-
A.
Lefuel
chosen
Lefuel is a French surname most notably associated with Hector Lefuel, a 19th-century architect known for his work on the Louvre in Paris.
-
B.
Mr. Fuel
Mr. Fuel is a fuel and convenience store brand operated by Pilot Flying J, serving highway travelers with gasoline, diesel, and travel amenities.
-
C.
Musina
Musina is a northern South African town in Limpopo Province, known as a key border and transport hub near Zimbabwe and for its history of copper and iron ore mining.
-
D.
Founex
Founex is a small Swiss municipality on Lake Geneva in the canton of Vaud, known for its residential character and proximity to Geneva.
-
E.
Fuhse
Fuhse is a river in Lower Saxony, Germany, that flows through several towns before joining the Aller River.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85aab0308190990626cbc9da3e21 |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18b75c388190955e4e31d71ffedb |
completed | March 21, 2026, 10:16 p.m. |
Created at: March 20, 2026, 2 p.m.