Triple
T2314150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SETL |
E51023
|
entity |
| Predicate | hasSuccessor |
P78
|
FINISHED |
| Object | SETLX |
E255546
|
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: SETLX | Statement: [SETL, hasSuccessor, SETLX]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SETLX Context triple: [SETL, hasSuccessor, SETLX]
-
A.
SETLX
chosen
SETLX is a modern, open-source programming language designed for teaching and experimenting with set theory and mathematical concepts through executable code.
-
B.
SETL
SETL is a high-level programming language developed in the late 1960s that is notable for its powerful set-theoretic abstractions and influence on later language design.
-
C.
TXL
TXL was the IATA airport code for Berlin Tegel Airport, the former main international airport of Berlin, Germany.
-
D.
LX
LX is the second-generation Holden Torana series produced in the mid-1970s, notable for introducing the A9X performance package and being a popular Australian mid-size car in both road and racing forms.
-
E.
LX
LX is the IATA airline designator used to identify Swiss International Air Lines on tickets, timetables, and flight numbers.
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc61d41f88190983f8947667b4c7a |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9610b420819095afb76347ddf9ee |
completed | March 9, 2026, 9:42 a.m. |
Created at: March 4, 2026, 7:49 p.m.