Triple
T16448547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Val Venosta |
E399493
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Lasa |
E1213202
|
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: Lasa | Statement: [Val Venosta, contains, Lasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lasa Context triple: [Val Venosta, contains, Lasa]
-
A.
Lasa
chosen
Lasa is a municipality in South Tyrol in northern Italy, known for its high-quality white marble quarries.
-
B.
Lasa
Lasa is a minor Etruscan goddess associated with protection, fate, and often depicted as an attendant or companion to other deities in Etruscan religious art.
-
C.
Lapwai
Lapwai is a small city in north-central Idaho that serves as the seat of the Nez Perce Indian Reservation and a cultural center for the Nez Perce Tribe.
-
D.
Mesa
Mesa is a pioneering systems programming language developed at Xerox PARC in the 1970s, notable for its strong typing, modularity, and influence on later languages and operating system design.
-
E.
Blythe
Blythe is a small desert city in Southern California near the Arizona border, known as a stopover along Interstate 10 by the Colorado River.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32cdee44c8190ae0df20c58ff7558 |
completed | April 18, 2026, 7:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f4b738881908f8a205466397f33 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.