Triple
T22765422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eusebio Francisco Kino |
E563110
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Segno |
—
|
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: Segno | Statement: [Eusebio Francisco Kino, placeOfBirth, Segno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Segno Context triple: [Eusebio Francisco Kino, placeOfBirth, Segno]
-
A.
Signo
Signo is a popular line of gel ink pens produced by Mitsubishi Pencil Company, known for their smooth writing performance and vibrant, long-lasting colors.
-
B.
Segni
chosen
Segni is an ancient hilltop town in the Lazio region of central Italy, known for its well-preserved polygonal walls and historic Roman and medieval heritage.
-
C.
Signum
Signum is a Swiss train protection and signaling system used to enhance the safety and control of railway operations.
-
D.
Seignosse
Seignosse is a coastal commune in southwestern France known for its Atlantic beaches, surf spots, and pine forests.
-
E.
Segny
Segny is a small commune in eastern France, located in the Ain department near the Swiss border and the city of Geneva.
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a80249c819091569e7b8d500b45 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:26 p.m.