Triple
T370879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Pulitzer |
E8265
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Mako, Hungary |
E46907
|
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: Mako, Hungary | Statement: [Joseph Pulitzer, birthPlace, Mako, Hungary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mako, Hungary Context triple: [Joseph Pulitzer, birthPlace, Mako, Hungary]
-
A.
Mako, Kingdom of Hungary
chosen
Mako, Kingdom of Hungary was a town in the former Kingdom of Hungary, notable as the birthplace of newspaper publisher and journalist Joseph Pulitzer.
-
B.
Miskolc
Miskolc is a large industrial and cultural city in northeastern Hungary, known for its steel industry, historic center, and nearby cave baths.
-
C.
Anif, Austria
Anif, Austria is a small municipality near Salzburg known for its picturesque setting and as the final resting place of famed conductor Herbert von Karajan.
-
D.
Volkerak
Volkerak is a lake and former estuarine channel in the southwestern Netherlands that forms part of the country’s major Rhine–Meuse–Scheldt waterway system.
-
E.
Karinska
Karinska was a renowned 20th-century costume designer best known for her influential work in ballet and theater, particularly with the New York City Ballet.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebff472881909fad81d597425ea6 |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3f0a78c748190ae5e64919f1d6501 |
completed | March 1, 2026, 7:54 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.