Triple
T12055705
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grabs |
E287035
|
entity |
| Predicate | sharesBorderWith |
P224
|
FINISHED |
| Object | Planken |
E487167
|
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: Planken | Statement: [Grabs, sharesBorderWith, Planken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Planken Context triple: [Grabs, sharesBorderWith, Planken]
-
A.
Planken
chosen
Planken is a small mountainous municipality in Liechtenstein known for its rural character and scenic alpine surroundings.
-
B.
Tábua
Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
-
C.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
-
D.
Tahta
Tahta is a city in Upper Egypt located within the Sohag Governorate, known as a regional center for agriculture and local trade along the Nile.
-
E.
Schaal
Schaal is a surname most notably associated with American actress Wendy Schaal, known for her work in film and television voice acting.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90425258c8190ba7b3b837c439253 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f64f40388190bfb3d2a81d5fbf5e |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:47 p.m.