Triple
T22305084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Wicker |
E551353
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wicker
Wicker is a surname of English origin borne by various notable individuals, including journalists, politicians, and public figures.
|
E1530427
|
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: Wicker | Statement: [Tom Wicker, familyName, Wicker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wicker Context triple: [Tom Wicker, familyName, Wicker]
-
A.
Weeden
Weeden is a surname most notably associated with Brandon Weeden, an American football quarterback who played in the NFL.
-
B.
Rattan
Rattan is a classic 1944 Hindi musical romance film, celebrated for its hit songs and for establishing composer Naushad as a major figure in Indian cinema.
-
C.
Webbwood
Webbwood is a small community in Ontario, Canada, known historically as a railway and logging town within the Sables-Spanish Rivers area.
-
D.
Weavercraft
Weavercraft is a Pernese professional craft dedicated to the design, production, and maintenance of textiles, clothing, and related woven goods across the planet’s Holds and Weyrs.
-
E.
Wood End
Wood End is a residential neighborhood located within the town of Hayes in west London, England.
- 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: Wicker Triple: [Tom Wicker, familyName, Wicker]
Generated description
Wicker is a surname of English origin borne by various notable individuals, including journalists, politicians, and public figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wicker Target entity description: Wicker is a surname of English origin borne by various notable individuals, including journalists, politicians, and public figures.
-
A.
Weeden
Weeden is a surname most notably associated with Brandon Weeden, an American football quarterback who played in the NFL.
-
B.
Rattan
Rattan is a classic 1944 Hindi musical romance film, celebrated for its hit songs and for establishing composer Naushad as a major figure in Indian cinema.
-
C.
Webbwood
Webbwood is a small community in Ontario, Canada, known historically as a railway and logging town within the Sables-Spanish Rivers area.
-
D.
Weavercraft
Weavercraft is a Pernese professional craft dedicated to the design, production, and maintenance of textiles, clothing, and related woven goods across the planet’s Holds and Weyrs.
-
E.
Wood End
Wood End is a residential neighborhood located within the town of Hayes in west London, England.
- 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_69e11e46c0188190800181a4233f28fe |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15726b7e48190b7636db01dbb8a40 |
completed | April 29, 2026, 12:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0acc9f16608190b6d1118238f96584 |
completed | May 18, 2026, 8:23 a.m. |
| NEDg | Description generation | batch_6a0acec65ef48190a9961d2c03361258 |
completed | May 18, 2026, 8:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0acf8273388190ba99a4d5900a7cce |
completed | May 18, 2026, 8:36 a.m. |
Created at: April 16, 2026, 8:41 p.m.