Triple
T13735427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Poliça |
E329930
|
entity |
| Predicate | hasEP |
P22078
|
FINISHED |
| Object | Tiff |
E252328
|
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: Tiff | Statement: [Poliça, hasEP, Tiff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiff Context triple: [Poliça, hasEP, Tiff]
-
A.
Tiff
chosen
Tiff is a common shortened form of the given name Tiffany, often used as a casual or affectionate nickname.
-
B.
TIF
TIF is the former New York Stock Exchange ticker symbol for Tiffany & Co., the luxury jewelry and specialty retailer.
-
C.
TIF
TIF is a major annual international trade fair held in Thessaloniki, Greece, showcasing products, services, and innovations from domestic and global exhibitors.
-
D.
TIF
TIF is the IATA airport code for Taif Regional Airport, which serves the city of Taif in Saudi Arabia.
-
E.
TIFF
TIFF is the non-profit cultural organization that runs the Toronto International Film Festival and related year-round film programs and events.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de020351fc8190a554a48c552e83b5 |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7a84dbdc48190a4724bb9c3523b25 |
completed | May 3, 2026, 7:55 p.m. |
Created at: April 9, 2026, 9:55 p.m.