Triple
T9766271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betuwe |
E236999
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object | Buren |
E328878
|
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: Buren | Statement: [Betuwe, hasSubregion, Buren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buren Context triple: [Betuwe, hasSubregion, Buren]
-
A.
Buren
chosen
Buren is a historic Dutch town in the province of Gelderland, known for its ties to the Dutch royal family and its well-preserved medieval character.
-
B.
Buren
Buren is the entomologist who formally described the invasive red imported fire ant species Solenopsis invicta.
-
C.
Montesson
Montesson is a suburban commune in the Yvelines department of north-central France, located to the northwest of Paris along the Seine River.
-
D.
Boissière
Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
-
E.
Prunelart
Prunelart is a rare, traditional red wine grape variety from southwest France, historically associated with the Gaillac region and valued for producing deeply colored, robust wines.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a15e408190909745cb1c30937d |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcf965e88190b505ce160f77e9b7 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:25 p.m.