Triple
T16621869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mats Zuccarello |
E403851
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Mats |
E347006
|
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: Mats | Statement: [Mats Zuccarello, givenName, Mats]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mats Context triple: [Mats Zuccarello, givenName, Mats]
-
A.
Mats
chosen
Mats is a masculine given name commonly used in Scandinavian countries, particularly Sweden and Norway.
-
B.
Mattsies
Mattsies is a village in Bavaria, Germany, known as the home base of the aircraft manufacturer Grob Aircraft AG.
-
C.
Matanvat
Matanvat is a village where the Nese language is traditionally spoken.
-
D.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
E.
Matsesta
Matsesta is a spa and resort area near Sochi on Russia’s Black Sea coast, historically renowned for its therapeutic sulfur springs.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754e80ec8190b3c66b33dbc7463c |
completed | April 18, 2026, 12:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007db27f788190a3c57b7ea8a8a9c6 |
completed | May 10, 2026, 12:44 p.m. |
Created at: April 10, 2026, 5:17 a.m.