Triple
T9463911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terina |
E228219
|
entity |
| Predicate | hasNameInItalian |
P17612
|
FINISHED |
| Object | Terina |
E228219
|
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: Terina | Statement: [Terina, hasNameInItalian, Terina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terina Context triple: [Terina, hasNameInItalian, Terina]
-
A.
Terina
chosen
Terina was an ancient Greek-founded city in southern Italy’s Bruttium region, known as a significant coastal and commercial center in Magna Graecia.
-
B.
Tenea
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
-
C.
Terêna
Terêna is an Arawakan language spoken by the Terena Indigenous people of Brazil, primarily in the state of Mato Grosso do Sul.
-
D.
Tianeti
Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
-
E.
Teri
Teri is a central character in the film and television series "Soul Food," known as the ambitious, high-powered attorney whose strained relationships with her family drive much of the story’s drama.
- 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_69ca846fee388190a6ec273fd644b88b |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fcec2d88190b93b6e4d881c85c6 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122a75aa08190adfe03d9f785f1ff |
completed | April 4, 2026, 2:39 p.m. |
Created at: March 30, 2026, 7:53 p.m.