Triple
T16969265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trowbridge |
E411622
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Oujda |
E443613
|
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: Oujda | Statement: [Trowbridge, hasTwinTown, Oujda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oujda Context triple: [Trowbridge, hasTwinTown, Oujda]
-
A.
Oujda
chosen
Oujda is a major city in northeastern Morocco near the Algerian border, known as an important commercial and cultural center of the region.
-
B.
Laayoune
Laayoune is the largest city and de facto administrative center of Western Sahara, located in the northwest of the disputed territory near the Atlantic coast.
-
C.
Aïn M’lila
Aïn M’lila is a city in northeastern Algeria known as a regional commercial and transportation hub.
-
D.
Sefrou
Sefrou is a historic town in northern Morocco known for its traditional medina, cherry festival, and location near the Middle Atlas mountains.
-
E.
Cherchell
Cherchell is a historic coastal town in northern Algeria, known for its ancient Phoenician and Roman heritage and its role as a cultural center in the region.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a86c64819092831f8ddf1e536b |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01232d6360819080ac00b8e56f098d |
completed | May 11, 2026, 12:30 a.m. |
Created at: April 10, 2026, 5:31 a.m.