Triple
T1960094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Filipa Moniz Perestrelo |
E42364
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Perestrelo
Perestrelo is a Portuguese surname historically associated with a noble family involved in early Atlantic exploration and linked by marriage to Christopher Columbus.
|
E219302
|
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: Perestrelo | Statement: [Filipa Moniz Perestrelo, familyName, Perestrelo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perestrelo Context triple: [Filipa Moniz Perestrelo, familyName, Perestrelo]
-
A.
Lastochka
Lastochka is a modern Russian electric multiple-unit passenger train brand used primarily for high-speed suburban and regional services.
-
B.
Bisher Bashi
Bisher Bashi is a renowned Bengali poetry collection by Kazi Nazrul Islam, noted for its intense emotional expression and revolutionary themes.
-
C.
Mishenka
Mishenka is a Russian affectionate diminutive form of the male given name Mikhail.
-
D.
Navolato
Navolato is a coastal agricultural city and municipality in the Mexican state of Sinaloa, known especially for its sugarcane production.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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: Perestrelo Triple: [Filipa Moniz Perestrelo, familyName, Perestrelo]
Generated description
Perestrelo is a Portuguese surname historically associated with a noble family involved in early Atlantic exploration and linked by marriage to Christopher Columbus.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Perestrelo Target entity description: Perestrelo is a Portuguese surname historically associated with a noble family involved in early Atlantic exploration and linked by marriage to Christopher Columbus.
-
A.
Lastochka
Lastochka is a modern Russian electric multiple-unit passenger train brand used primarily for high-speed suburban and regional services.
-
B.
Bisher Bashi
Bisher Bashi is a renowned Bengali poetry collection by Kazi Nazrul Islam, noted for its intense emotional expression and revolutionary themes.
-
C.
Mishenka
Mishenka is a Russian affectionate diminutive form of the male given name Mikhail.
-
D.
Navolato
Navolato is a coastal agricultural city and municipality in the Mexican state of Sinaloa, known especially for its sugarcane production.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb37f737881908130bb828affcaa2 |
completed | March 7, 2026, 5:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfbcea048819091d705095f0d3f68 |
completed | March 8, 2026, 10:44 p.m. |
| NEDg | Description generation | batch_69adfc8efb0c81908bce5a4a13359801 |
completed | March 8, 2026, 10:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adfd8115d481909716e11b943cbf61 |
completed | March 8, 2026, 10:51 p.m. |
Created at: March 4, 2026, 7:36 p.m.