Triple
T188815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre |
E3672
|
entity |
| Predicate | cognateWith |
P2525
|
FINISHED |
| Object |
Pietro
Pietro is the Italian given name equivalent to "Peter," commonly used in Italy and among Italian-speaking communities.
|
E29219
|
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: Pietro | Statement: [Pierre, cognateWith, Pietro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pietro Context triple: [Pierre, cognateWith, Pietro]
-
A.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
B.
Guglielmi
Guglielmi is the Italian surname of silent film icon Rudolph Valentino, reflecting his family’s origins.
-
C.
Guido
Guido is a masculine given name of Italian origin, famously borne by Guido van Rossum, the creator of the Python programming language.
-
D.
Antonio Quarracino
Antonio Quarracino was an Argentine cardinal of the Roman Catholic Church who served as Archbishop of Buenos Aires and played a key role in the ecclesiastical career of Pope Francis.
-
E.
Louis Appia
Louis Appia was a 19th-century Swiss surgeon and humanitarian pioneer who helped establish the principles and institutions that became the modern Red Cross movement.
- 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: Pietro Triple: [Pierre, cognateWith, Pietro]
Generated description
Pietro is the Italian given name equivalent to "Peter," commonly used in Italy and among Italian-speaking communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pietro Target entity description: Pietro is the Italian given name equivalent to "Peter," commonly used in Italy and among Italian-speaking communities.
-
A.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
-
B.
Guglielmi
Guglielmi is the Italian surname of silent film icon Rudolph Valentino, reflecting his family’s origins.
-
C.
Guido
Guido is a masculine given name of Italian origin, famously borne by Guido van Rossum, the creator of the Python programming language.
-
D.
Antonio Quarracino
Antonio Quarracino was an Argentine cardinal of the Roman Catholic Church who served as Archbishop of Buenos Aires and played a key role in the ecclesiastical career of Pope Francis.
-
E.
Louis Appia
Louis Appia was a 19th-century Swiss surgeon and humanitarian pioneer who helped establish the principles and institutions that became the modern Red Cross movement.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25bc834388190a93ec1ab0d5946de |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a35b61bdfc8190a399f0b4f09672ab |
completed | Feb. 28, 2026, 9:17 p.m. |
| NEDg | Description generation | batch_69a35bda2f2881908451ac1861bc5e22 |
completed | Feb. 28, 2026, 9:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a35c7340d08190bdf142d265369af5 |
completed | Feb. 28, 2026, 9:21 p.m. |
Created at: Feb. 28, 2026, 2:41 a.m.