Triple
T11958158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GAS |
E284603
|
entity |
| Predicate | usedWith |
P4791
|
FINISHED |
| Object | GDB |
E59979
|
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: GDB | Statement: [GAS, usedWith, GDB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GDB Context triple: [GAS, usedWith, GDB]
-
A.
GDB
chosen
GDB is a powerful open-source debugger from the GNU Project used to analyze and control the execution of programs written in languages like C, C++, and Fortran.
-
B.
GDB
GDB is a German vehicle registration code assigned to the district of Nordwestmecklenburg in the state of Mecklenburg-Vorpommern.
-
C.
GNU Debugger
GNU Debugger (GDB) is a widely used free and open-source debugging tool for programs written in languages like C, C++, and Fortran, allowing developers to inspect and control program execution.
-
D.
GDK
GDK is the low-level drawing and windowing system library that underpins GTK, providing an abstraction layer over the underlying graphical system.
-
E.
DBG
DBG is the Indian Railways station code for Darbhanga Junction, a major railway station in the city of Darbhanga in Bihar, India.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903681a00819098c2b5260e2ef834 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f459210d1c8190953cd01da3d2ad04 |
completed | May 1, 2026, 7:41 a.m. |
Created at: April 8, 2026, 9:45 p.m.