Triple
T19717045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archaic period |
E473503
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Pythagoras |
—
|
NE NERFINISHED |
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: Pythagoras | Statement: [Archaic period, associatedWith, Pythagoras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pythagoras Context triple: [Archaic period, associatedWith, Pythagoras]
-
A.
Pythagoras
chosen
Pythagoras was an ancient Greek philosopher and mathematician best known for founding the Pythagorean school and for the Pythagorean theorem in geometry.
-
B.
Pythagoras of Rhegion
Pythagoras of Rhegion was an ancient Greek sculptor renowned for his realistic bronze statues and is traditionally credited with creating the famous Charioteer of Delphi.
-
C.
Pythagoreio
Pythagoreio is a historic coastal town and popular tourist resort on the Greek island of Samos, known for its ancient harbor and archaeological sites.
-
D.
Hippasus
Hippasus is a figure from Greek mythology known as one of the heroes who took part in the legendary Calydonian Boar Hunt.
-
E.
Thales
Thales is a major French multinational company specializing in aerospace, defense, security, and digital technologies.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e516dd048190a0b6c93ea3e71f58 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6440d96288190bfb732d2f8ceac79 |
completed | April 20, 2026, 3:19 p.m. |
Created at: April 10, 2026, 1:46 p.m.