Triple
T6739338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hachette UK |
E154033
|
entity |
| Predicate | hasImprint |
P2763
|
FINISHED |
| Object |
Virago
Virago is a British publishing imprint renowned for championing women’s writing and feminist literature.
|
E616752
|
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: Virago | Statement: [Hachette UK, hasImprint, Virago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Virago Context triple: [Hachette UK, hasImprint, Virago]
-
A.
Venucia
Venucia is a Chinese automobile marque known for producing affordable passenger vehicles, originally established as a local brand under the Renault–Nissan–Mitsubishi Alliance.
-
B.
Vespa
Vespa is a genus of large social wasps best known for including the true hornets found across Europe and Asia.
-
C.
Vomag
Vomag was a German vehicle manufacturer best known for producing military trucks and armored vehicles, including variants of the Panzer IV, during the World War II era.
-
D.
Griante
Griante is a small lakeside village on Lake Como in Lombardy, Italy, known for its scenic views and historic villas.
-
E.
Vixen
Vixen is an American all-female glam metal band best known for their late-1980s hits and self-titled debut album.
- 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: Virago Triple: [Hachette UK, hasImprint, Virago]
Generated description
Virago is a British publishing imprint renowned for championing women’s writing and feminist literature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Virago Target entity description: Virago is a British publishing imprint renowned for championing women’s writing and feminist literature.
-
A.
Venucia
Venucia is a Chinese automobile marque known for producing affordable passenger vehicles, originally established as a local brand under the Renault–Nissan–Mitsubishi Alliance.
-
B.
Vespa
Vespa is a genus of large social wasps best known for including the true hornets found across Europe and Asia.
-
C.
Vespa
Vespa is an iconic Italian brand of motor scooters known for its distinctive design and widespread popularity in urban transportation.
-
D.
Vomag
Vomag was a German vehicle manufacturer best known for producing military trucks and armored vehicles, including variants of the Panzer IV, during the World War II era.
-
E.
Griante
Griante is a small lakeside village on Lake Como in Lombardy, Italy, known for its scenic views and historic villas.
- 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_69c6880d84d8819095d19de2295f26ac |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d187c8788190b9fc1ebc9a66a520 |
completed | March 27, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b0db3f481909b5281c63cc32dd1 |
completed | March 27, 2026, 10:56 p.m. |
| NEDg | Description generation | batch_69c70b83f24c819091a6a2a7802c830f |
completed | March 27, 2026, 10:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c70f676e408190bc85a2760446d5d1 |
completed | March 27, 2026, 11:14 p.m. |
Created at: March 27, 2026, 2:10 p.m.