Triple
T6565461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernard Freyberg |
E153891
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Tiny |
E153891
|
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: Tiny | Statement: [Bernard Freyberg, nickname, Tiny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiny Context triple: [Bernard Freyberg, nickname, Tiny]
-
A.
Tiny
chosen
Tiny was the ironic nickname of Bernard Freyberg, a highly decorated British-New Zealand military commander and World War II general.
-
B.
Tiny
Tiny is the giant blue ox companion of the legendary lumberjack Paul Bunyan in American folklore.
-
C.
Mini
Mini is a young Bengali girl in Rabindranath Tagore’s short story "Kabuliwala," whose innocent friendship with an Afghan fruit seller forms the emotional core of the narrative.
-
D.
Mini
Mini is a British automotive marque best known for its compact, stylish small cars that originated with the iconic Mini of the 1960s.
-
E.
Little
Little is a 2019 fantasy-comedy film in which a domineering tech executive is magically transformed into her younger self, forcing her to relive middle school and confront her past behavior.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae3cc05881908e943d3f7f8a2b1d |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d5622e0481909b0ac0f4e06d19bc |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:52 p.m.