Triple
T23443400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Possible |
E565466
|
entity |
| Predicate | hasSupportingCharacter |
P7748
|
FINISHED |
| Object |
Wade Load
Wade Load is the tech-savvy teenage genius who remotely assists Kim Possible on her missions by providing gadgets, intel, and computer support.
|
E1587338
|
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: Wade Load | Statement: [Kim Possible, hasSupportingCharacter, Wade Load]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wade Load Context triple: [Kim Possible, hasSupportingCharacter, Wade Load]
-
A.
Waddy
Waddy is a given name most notably borne by the American architect Waddy Butler Wood.
-
B.
Wadee
Wadee is a given name, likely a variant of the name Wade, used as a personal first name.
-
C.
Watkins
Watkins is a surname most prominently associated with Sherron Watkins, the former Enron vice president who became widely known as a corporate whistleblower.
-
D.
Vandover
Vandover is the troubled protagonist of Frank Norris's novel "Vandover and the Brute," whose moral and psychological decline explores themes of degeneration and inner savagery.
-
E.
That Dam
That Dam is an ancient, dark-stoned Buddhist stupa in central Vientiane, Laos, surrounded by local legends and considered one of the city’s most historic religious monuments.
- 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: Wade Load Triple: [Kim Possible, hasSupportingCharacter, Wade Load]
Generated description
Wade Load is the tech-savvy teenage genius who remotely assists Kim Possible on her missions by providing gadgets, intel, and computer support.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wade Load Target entity description: Wade Load is the tech-savvy teenage genius who remotely assists Kim Possible on her missions by providing gadgets, intel, and computer support.
-
A.
Waddy
Waddy is a given name most notably borne by the American architect Waddy Butler Wood.
-
B.
Wadee
Wadee is a given name, likely a variant of the name Wade, used as a personal first name.
-
C.
Watkins
Watkins is a surname most prominently associated with Sherron Watkins, the former Enron vice president who became widely known as a corporate whistleblower.
-
D.
Vandover
Vandover is the troubled protagonist of Frank Norris's novel "Vandover and the Brute," whose moral and psychological decline explores themes of degeneration and inner savagery.
-
E.
That Dam
That Dam is an ancient, dark-stoned Buddhist stupa in central Vientiane, Laos, surrounded by local legends and considered one of the city’s most historic religious monuments.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64717d08190a2c25e7bbfc17a2f |
completed | April 29, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c67b583fc8190941de49b824f9c98 |
completed | May 19, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_6a0c7217edc881909f582f0c726d7e61 |
completed | May 19, 2026, 2:22 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c770386a8819098358513016ae5ab |
completed | May 19, 2026, 2:43 p.m. |
Created at: April 17, 2026, 5:51 p.m.