Triple
T22769842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interlisp |
E563523
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
DWIM
DWIM (Do What I Mean) is an error-correcting and command-guessing feature in the Interlisp programming environment designed to interpret and automatically fix users’ likely mistakes.
|
E1553584
|
NE FINISHED |
How this triple was built (4 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: DWIM | Statement: [Interlisp, component, DWIM]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DWIM Context triple: [Interlisp, component, DWIM]
-
A.
DW
DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
-
B.
DW
DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
-
C.
DW
DW is the vehicle registration code used on license plates for the Sächsische Schweiz-Osterzgebirge district in the German state of Saxony.
-
D.
WYM
WYM is the National Rail station code for Wylam railway station in Northumberland, England.
-
E.
DWM
DWM is the Windows system component responsible for rendering and managing the visual effects and composition of the desktop user interface.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DWIM Triple: [Interlisp, component, DWIM]
Generated description
DWIM (Do What I Mean) is an error-correcting and command-guessing feature in the Interlisp programming environment designed to interpret and automatically fix users’ likely mistakes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DWIM Target entity description: DWIM (Do What I Mean) is an error-correcting and command-guessing feature in the Interlisp programming environment designed to interpret and automatically fix users’ likely mistakes.
-
A.
DW
DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
-
B.
DW
DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
-
C.
DW
DW is the vehicle registration code used on license plates for the Sächsische Schweiz-Osterzgebirge district in the German state of Saxony.
-
D.
WYM
WYM is the National Rail station code for Wylam railway station in Northumberland, England.
-
E.
DWM
DWM is the Windows system component responsible for rendering and managing the visual effects and composition of the desktop user interface.
- F. None of above. chosen
Provenance (5 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b5cea44819097290351da9c488d |
completed | April 29, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b982109788190acef5fb8cbb96c1b |
completed | May 18, 2026, 10:52 p.m. |
| NEDg | Description generation | batch_6a0b98f528288190b716963b91513895 |
completed | May 18, 2026, 10:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b99c5fba88190bfba0633a2e3c03b |
completed | May 18, 2026, 10:59 p.m. |
Created at: April 17, 2026, 3:27 p.m.