Triple
T16503187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyndon Loos |
E400849
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Loos |
E472561
|
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: Loos | Statement: [Lyndon Loos, hasFamilyName, Loos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loos Context triple: [Lyndon Loos, hasFamilyName, Loos]
-
A.
Loos
chosen
Loos is a commune in northern France that forms part of the Lille metropolitan area.
-
B.
Lobbes
Lobbes is a historic municipality in the Walloon region of Belgium, known for its ancient abbey and picturesque rural setting.
-
C.
La Hulpe
La Hulpe is a small, affluent municipality in Walloon Brabant, Belgium, known for its green surroundings and the Château de La Hulpe within the Solvay Regional Estate.
-
D.
Breda
Breda is an Italian industrial company best known for manufacturing railway rolling stock, including trains and trams used in transit systems worldwide.
-
E.
Breda
Breda is a historic city in the southern Netherlands known for its medieval architecture, former status as a military and political center, and vibrant cultural life.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e50436c8190836a1bc2baa188b1 |
completed | April 18, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00582e6e288190825af8758097e325 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:14 a.m.