Triple
T7464342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leer (district) |
E176335
|
entity |
| Predicate | capital |
P234
|
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: [Leer (district), capital, Leer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leer Context triple: [Leer (district), capital, 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.
Lezgin
Lezgin is a Northeast Caucasian language spoken primarily by the Lezgin people in southern Dagestan (Russia) and northern Azerbaijan.
-
D.
Lectoure
Lectoure is a historic town in southwestern France, in the Gers department of the Occitanie region, known for its medieval architecture and hilltop setting.
-
E.
Lleó
Lleó is a Spanish-language surname of Catalan origin borne by various individuals, including Cuban jurist and former president Manuel Urrutia Lleó.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d9d25c819087efc772b5b127fa |
completed | March 27, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8346adb3081908f049d8dcd623215 |
completed | March 28, 2026, 8:04 p.m. |
Created at: March 27, 2026, 3:40 p.m.