Triple
T1811964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tommy Hilfiger |
E40350
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Kathleen Hilfiger
Kathleen Hilfiger is one of the children of American fashion designer Tommy Hilfiger.
|
E208765
|
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: Kathleen Hilfiger | Statement: [Tommy Hilfiger, hasChild, Kathleen Hilfiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kathleen Hilfiger Context triple: [Tommy Hilfiger, hasChild, Kathleen Hilfiger]
-
A.
Tina Hirsch
Tina Hirsch is an American film editor known for her work on numerous feature films and television projects.
-
B.
Susie Hilfiger
Susie Hilfiger is an American businesswoman and former wife of fashion designer Tommy Hilfiger, known for her involvement in the fashion and lifestyle industry.
-
C.
Ally Hilfiger
Ally Hilfiger is an American artist, television personality, and fashion designer best known for starring in the MTV reality series "Rich Girls" and as the daughter of fashion designer Tommy Hilfiger.
-
D.
Virginia Katz
Virginia Katz is a film editor known for her work on major Hollywood productions, including entries in the Twilight Saga.
-
E.
Marcia Reale
Marcia Reale was the royal anthem of the Kingdom of Italy, closely associated with the Italian monarchy and official state ceremonies before the republic was established.
- 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: Kathleen Hilfiger Triple: [Tommy Hilfiger, hasChild, Kathleen Hilfiger]
Generated description
Kathleen Hilfiger is one of the children of American fashion designer Tommy Hilfiger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kathleen Hilfiger Target entity description: Kathleen Hilfiger is one of the children of American fashion designer Tommy Hilfiger.
-
A.
Tina Hirsch
Tina Hirsch is an American film editor known for her work on numerous feature films and television projects.
-
B.
Susie Hilfiger
Susie Hilfiger is an American businesswoman and former wife of fashion designer Tommy Hilfiger, known for her involvement in the fashion and lifestyle industry.
-
C.
Ally Hilfiger
Ally Hilfiger is an American artist, television personality, and fashion designer best known for starring in the MTV reality series "Rich Girls" and as the daughter of fashion designer Tommy Hilfiger.
-
D.
Virginia Katz
Virginia Katz is a film editor known for her work on major Hollywood productions, including entries in the Twilight Saga.
-
E.
Marcia Reale
Marcia Reale was the royal anthem of the Kingdom of Italy, closely associated with the Italian monarchy and official state ceremonies before the republic was established.
- 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_69a88643a3388190a612f2ebe1fb29e7 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa65c64bc08190b993216890752b46 |
completed | March 6, 2026, 5:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1bd5f68819080a4fe06e3e1f76d |
completed | March 8, 2026, 7:45 p.m. |
| NEDg | Description generation | batch_69add229de448190826bbb668c7611a0 |
completed | March 8, 2026, 7:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69add29e3c50819098ff87d254c25c45 |
completed | March 8, 2026, 7:48 p.m. |
Created at: March 4, 2026, 7:32 p.m.