Triple
T7669219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Pescara |
E173704
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Penne |
E403321
|
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: Penne | Statement: [Province of Pescara, contains, Penne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penne Context triple: [Province of Pescara, contains, Penne]
-
A.
Penne
chosen
Penne is a historic hill town in Italy’s Abruzzo region, notable for its ancient Vestini roots and well-preserved medieval architecture.
-
B.
Macaroni
Macaroni was a notable 19th-century British Thoroughbred racehorse and influential sire in bloodlines of classic winners.
-
C.
Spaghettii
"Spaghettii" is a song by Beyoncé from her genre-blending album "Cowboy Carter," showcasing her experimental approach to country and hip-hop influences.
-
D.
Linguini
Linguini is the clumsy yet kind-hearted young chef from Disney-Pixar’s Ratatouille who secretly teams up with the rat Remy to create extraordinary dishes.
-
E.
Prego
Prego is a popular American brand of pasta sauces known for its thick, tomato-based varieties and wide range of flavors.
- 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701c3ff38819090d65ac4ae218750 |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89b29232c81908568eda38c2ac12a |
completed | March 29, 2026, 3:23 a.m. |
Created at: March 27, 2026, 4 p.m.