Triple
T14415278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 8310 |
E357433
|
entity |
| Predicate | includesGame |
P1393
|
FINISHED |
| Object | Pairs II |
E997036
|
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: Pairs II | Statement: [Nokia 8310, includesGame, Pairs II]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pairs II Context triple: [Nokia 8310, includesGame, Pairs II]
-
A.
Pairs II
chosen
Pairs II is a simple matching puzzle game featured among the built-in titles on the Nokia 3510 mobile phone.
-
B.
PairGrid
PairGrid is a Seaborn class for creating multi-plot grids that visualize pairwise relationships across multiple variables in a dataset.
-
C.
Paar
Paar is a surname most notably associated with American television host and comedian Jack Paar, a pioneering figure of late-night talk shows.
-
D.
Paar
"Paar" is a critically acclaimed Indian film directed by Goutam Ghose, known for its stark portrayal of social injustice and rural hardship.
-
E.
Paar
Paar is a river in Bavaria, Germany, known for flowing through several towns and rural landscapes before joining the Danube.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cc99208190a2313b1acfb5d802 |
completed | April 14, 2026, 7:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd552a75ec8190b966d509d315ca60 |
completed | May 8, 2026, 3:14 a.m. |
Created at: April 10, 2026, 1:17 a.m.