Triple
T13574191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MKS Cracovia |
E324239
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Pasy |
E320393
|
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: Pasy | Statement: [MKS Cracovia, nickname, Pasy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasy Context triple: [MKS Cracovia, nickname, Pasy]
-
A.
Pasy
chosen
Pasy is the popular nickname of the Polish football club Cracovia, one of the oldest and most historic teams in Poland.
-
B.
Pasym
Pasym is a small historic town in northern Poland known for its lakeside setting and traditional Warmian-Masurian architecture.
-
C.
Pas
Pas is a river in northern Spain that flows through the region of Cantabria and is known for its scenic valleys and traditional rural landscapes.
-
D.
PAS
PAS is a key instrument within the Solar Wind Analyser suite designed to measure the properties of solar wind particles, such as their velocity distribution, density, and temperature.
-
E.
Pasil
Pasil is a rural municipality in the mountainous province of Kalinga in the Philippines, known for its indigenous communities and rice-terraced landscapes.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb02b1f108190a12af382d1de70bb |
completed | April 12, 2026, 2:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bb827d48190958e5710d554cd04 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.