Triple
T16912450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fernando |
E410234
|
entity |
| Predicate | hasShortForm |
P43
|
FINISHED |
| Object |
Nandinho
Nandinho is a Portuguese diminutive nickname commonly used for people named Fernando.
|
E1239812
|
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: Nandinho | Statement: [Fernando, hasShortForm, Nandinho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nandinho Context triple: [Fernando, hasShortForm, Nandinho]
-
A.
Mirambo
Mirambo was a powerful 19th-century Nyamwezi warlord and trader in present-day Tanzania, known for building a strong kingdom and controlling key caravan trade routes.
-
B.
Bul Nuer
Bul Nuer is a dialect of the Nuer language spoken by a subgroup of the Nuer people in South Sudan and neighboring regions.
-
C.
Dja-et-Lobo
Dja-et-Lobo is a department in the South Region of Cameroon known for its largely forested landscape and low population density.
-
D.
Bandila
Bandila is a late-night Philippine television news program produced by ABS-CBN News and Current Affairs, known for its in-depth reporting and coverage of major national events.
-
E.
Uma Mbatangu
Uma Mbatangu is a traditional Sumbanese house type characterized by its tall peaked thatched roof and elevated wooden structure, commonly found in the Waikabubak area of Indonesia.
- 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: Nandinho Triple: [Fernando, hasShortForm, Nandinho]
Generated description
Nandinho is a Portuguese diminutive nickname commonly used for people named Fernando.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nandinho Target entity description: Nandinho is a Portuguese diminutive nickname commonly used for people named Fernando.
-
A.
Mirambo
Mirambo was a powerful 19th-century Nyamwezi warlord and trader in present-day Tanzania, known for building a strong kingdom and controlling key caravan trade routes.
-
B.
Bul Nuer
Bul Nuer is a dialect of the Nuer language spoken by a subgroup of the Nuer people in South Sudan and neighboring regions.
-
C.
Dja-et-Lobo
Dja-et-Lobo is a department in the South Region of Cameroon known for its largely forested landscape and low population density.
-
D.
Bandila
Bandila is a late-night Philippine television news program produced by ABS-CBN News and Current Affairs, known for its in-depth reporting and coverage of major national events.
-
E.
Uma Mbatangu
Uma Mbatangu is a traditional Sumbanese house type characterized by its tall peaked thatched roof and elevated wooden structure, commonly found in the Waikabubak area of Indonesia.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3e6b9481909fbaeb0bddd7e3b2 |
completed | April 18, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00c7bb4ac481909318d3d61a2d10e1 |
completed | May 10, 2026, 6 p.m. |
| NEDg | Description generation | batch_6a00c8c9c78481908e503977d47f7c1f |
completed | May 10, 2026, 6:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00c9d1c6a0819083635b8246cc82e7 |
completed | May 10, 2026, 6:09 p.m. |
Created at: April 10, 2026, 5:30 a.m.