Triple
T18998817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LIPZ |
E464890
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tessera |
—
|
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: Tessera | Statement: [LIPZ, locatedIn, Tessera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessera Context triple: [LIPZ, locatedIn, Tessera]
-
A.
Tessera
chosen
Tessera is a mainland district of Venice, Italy, best known as the site of Venice Marco Polo Airport.
-
B.
Tessera
Tessera is a privacy and transaction manager for Ethereum-based networks, commonly used with Hyperledger Besu to enable private and confidential smart contract transactions.
-
C.
Tisean
Tisean is one of the four close friends in the 1996 crime film "Set It Off," whose personal struggles and loyalty drive much of the movie’s emotional core.
-
D.
The Spiral
"The Spiral" is a short story by Italo Calvino, included in his collection *Cosmicomics*, that blends imaginative science fiction with playful philosophical reflection on evolution and existence.
-
E.
Tetrada
Tetrada is a municipal unit within the Georgios Karaiskakis municipality in the Epirus region of western Greece.
- 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_69d8dd01a56c81909694a128c66b21d7 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6838f4481909b265e29964b0dca |
completed | April 20, 2026, 7:32 a.m. |
Created at: April 10, 2026, 12:01 p.m.