Triple
T7724727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristina Pato |
E175100
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pato |
E684486
|
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: Pato | Statement: [Cristina Pato, familyName, Pato]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pato Context triple: [Cristina Pato, familyName, Pato]
-
A.
Pato
chosen
Pato is a Galician musician and educator best known internationally as a virtuoso gaita (Galician bagpipe) player and collaborator with jazz and classical ensembles.
-
B.
Pichi
Pichi is an English-based creole language spoken primarily on the island of Bioko in Equatorial Guinea.
-
C.
Pombo
Pombo is a component or subdivision associated with the larger entity known as Linares y Pombo.
-
D.
Patos
Patos is a municipality in the state of Paraíba in northeastern Brazil, known as a regional commercial and service center in the semi-arid hinterland.
-
E.
Pidgeon
Pidgeon is a surname most notably associated with Canadian-American actor Walter Pidgeon, a prominent film star of Hollywood’s classic era.
- 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_69c6995d541c81909eaa646b1a8369a9 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7031279708190a3a5fb64f9206974 |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8be2de08881909715d9164b743aae |
completed | March 29, 2026, 5:52 a.m. |
Created at: March 27, 2026, 4:05 p.m.