Triple
T8751597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massa |
E207971
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Carrara |
E151864
|
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: Carrara | Statement: [Massa, locatedNear, Carrara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carrara Context triple: [Massa, locatedNear, Carrara]
-
A.
Carrara
chosen
Carrara is an Italian city renowned worldwide for its high-quality white marble quarries and sculpture tradition.
-
B.
Carrara
Carrara is a suburb on Queensland’s Gold Coast in Australia, known for its residential communities, golf courses, and proximity to major sporting and entertainment venues.
-
C.
Cortona
Cortona is an ancient hilltop town in Tuscany, Italy, historically significant as one of the principal cities of the Etruscan civilization.
-
D.
Cascia
Cascia is a historic hill town and pilgrimage site in the Umbria region of central Italy, best known for its association with Saint Rita of Cascia.
-
E.
Nocera Umbra
Nocera Umbra is a historic hill town in the Umbria region of central Italy, known for its medieval architecture and mineral 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_69ca835bb2bc819084bb5906cb6ef7f8 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5da774f4819099e5bfd12973d946 |
completed | March 31, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf4326d8cc8190900f5f91da6ef6c8 |
completed | April 3, 2026, 4:33 a.m. |
Created at: March 30, 2026, 6:39 p.m.