Triple
T9655263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zacarias Gusmão |
E233433
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gusmão |
E266574
|
NE FINISHED |
How this triple was built (2 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: Gusmão | Statement: [Zacarias Gusmão, familyName, Gusmão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gusmão Context triple: [Zacarias Gusmão, familyName, Gusmão]
-
A.
Gusmão
chosen
Gusmão is a Portuguese-origin surname notably borne by East Timorese independence leader and statesman Kay Rala Xanana Gusmão.
-
B.
Delmiro Gouveia
Delmiro Gouveia is a municipality in northeastern Brazil known for its historical association with early industrial development and the pioneering entrepreneur Delmiro Augusto da Cruz Gouveia.
-
C.
Mário Filho
Mário Filho was a prominent Brazilian sports journalist whose influence on football culture was so great that Rio de Janeiro’s iconic Maracanã Stadium was named in his honor.
-
D.
Costa Pinheiro
Costa Pinheiro was a Portuguese artist known for his contributions to contemporary painting and public art installations.
-
E.
Vicente José de Oliveira Muniz
Vicente José de Oliveira Muniz, better known as Vik Muniz, is a Brazilian contemporary artist renowned for creating intricate images using unconventional materials such as chocolate, sugar, garbage, and everyday objects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bdbdd948190a4545a5df0f7af77 |
completed | April 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f6d397481908f7db1f272a6a710 |
completed | April 4, 2026, 11:31 p.m. |
Created at: March 30, 2026, 8:13 p.m.