Triple
T12080467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arrondissement of Sélestat-Erstein |
E287662
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Barr |
E105937
|
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: Barr | Statement: [Arrondissement of Sélestat-Erstein, contains, Barr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barr Context triple: [Arrondissement of Sélestat-Erstein, contains, Barr]
-
A.
Barr
chosen
Barr is a surname and place name of Scottish and Irish origin, associated with various towns, geographic features, and notable individuals.
-
B.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
C.
Barron
Barron is a surname of English origin borne by various notable individuals across fields such as law, politics, and the arts.
-
D.
BARRY
BARRY is a coastal town in the Vale of Glamorgan, South Wales, known for its seaside resort, Barry Island, and proximity to Cardiff.
-
E.
Baar
Baar is a municipality in the canton of Zug in central Switzerland, known for its favorable tax environment and mix of residential areas and international businesses.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d904dc98a88190a5873f3fd8e1a0b2 |
completed | April 10, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66301f081909697f9dd444a099e |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.