Triple
T12044990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | How to Do Things with Words |
E286761
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object |
Marina Sbisa
Marina Sbisa is an Italian philosopher and linguist known for her influential work in pragmatics and speech act theory.
|
E961911
|
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: Marina Sbisa | Statement: [How to Do Things with Words, editor, Marina Sbisa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marina Sbisa Context triple: [How to Do Things with Words, editor, Marina Sbisa]
-
A.
Marina Umaschi Bers
Marina Umaschi Bers is a professor and researcher known for her pioneering work in early childhood computer science education and the development of child-friendly programming tools like ScratchJr and KIBO.
-
B.
Marina Severa
Marina Severa was a Roman empress of the 4th century, known as the first wife of Emperor Valentinian I and the mother of Emperor Gratian.
-
C.
Marina Chapelin
Marina Chapelin is a coastal marina in Varadero, Cuba, serving as a docking and service hub for recreational boats and yachts.
-
D.
Marisa Borini
Marisa Borini is an Italian concert pianist and actress, best known as the mother of singer-songwriter and former French First Lady Carla Bruni.
-
E.
Ines Glorian
Ines Glorian is the wife of Irish actor Colm Meaney.
- 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: Marina Sbisa Triple: [How to Do Things with Words, editor, Marina Sbisa]
Generated description
Marina Sbisa is an Italian philosopher and linguist known for her influential work in pragmatics and speech act theory.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Marina Sbisa Target entity description: Marina Sbisa is an Italian philosopher and linguist known for her influential work in pragmatics and speech act theory.
-
A.
Marina Umaschi Bers
Marina Umaschi Bers is a professor and researcher known for her pioneering work in early childhood computer science education and the development of child-friendly programming tools like ScratchJr and KIBO.
-
B.
Marina Severa
Marina Severa was a Roman empress of the 4th century, known as the first wife of Emperor Valentinian I and the mother of Emperor Gratian.
-
C.
Marina Chapelin
Marina Chapelin is a coastal marina in Varadero, Cuba, serving as a docking and service hub for recreational boats and yachts.
-
D.
Marisa Borini
Marisa Borini is an Italian concert pianist and actress, best known as the mother of singer-songwriter and former French First Lady Carla Bruni.
-
E.
Ines Glorian
Ines Glorian is the wife of Irish actor Colm Meaney.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9041fe3b0819094b82a6b17ac59c3 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49db574bc8190a0f2f858a2ff788d |
completed | May 1, 2026, 12:33 p.m. |
| NEDg | Description generation | batch_69f53d9460bc8190869f2b7d095d98cb |
completed | May 1, 2026, 11:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f564d2b4348190abf2d09ae00aea37 |
completed | May 2, 2026, 2:43 a.m. |
Created at: April 8, 2026, 9:47 p.m.