Triple
T16859444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyundai Tucson |
E409868
|
entity |
| Predicate | hasTrimLevel |
P2393
|
FINISHED |
| Object | Limited |
E918050
|
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: Limited | Statement: [Hyundai Tucson, hasTrimLevel, Limited]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limited Context triple: [Hyundai Tucson, hasTrimLevel, Limited]
-
A.
Limited
chosen
Limited is a higher-end, well-equipped trim level of the Toyota 4Runner SUV, featuring added comfort, technology, and luxury-oriented features.
-
B.
Few
Few is an English-language surname borne by various notable individuals, including American politician and Founding Father William Few.
-
C.
Minimum
"Minimum" is a book by British architect John Pawson that explores the principles and aesthetics of minimalism in architecture, design, and everyday objects.
-
D.
Less
Less is a dynamic stylesheet language that extends CSS with features like variables, mixins, and functions to make writing and maintaining styles more efficient.
-
E.
Vertical Limit
Vertical Limit is a 2000 action-thriller film about a high-stakes rescue mission on K2, known for its intense mountaineering sequences and starring Chris O'Donnell.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b501f72881909f7600311705fb33 |
completed | April 18, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb25300c8190a352037c21c244bd |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.