Triple
T16969263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trowbridge |
E411622
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Leer |
E176336
|
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: Leer | Statement: [Trowbridge, hasTwinTown, Leer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leer Context triple: [Trowbridge, hasTwinTown, Leer]
-
A.
Leer
chosen
Leer is a historic town in northwestern Germany known for its maritime heritage and traditional East Frisian culture.
-
B.
Lees
Lees is a village in the Metropolitan Borough of Oldham, Greater Manchester, England, historically part of Lancashire.
-
C.
Lees
Lees is the surname of Andrea Leeds, an American film actress prominent in the 1930s and 1940s.
-
D.
Lezgin
Lezgin is a Northeast Caucasian language spoken primarily by the Lezgin people in southern Dagestan (Russia) and northern Azerbaijan.
-
E.
Léez
Léez is a river in southwestern France that serves as a tributary within the Gave de Pau river system.
- 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_6a00d471d4248190acf40b6c11926a65 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:31 a.m.