Triple
T9226483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabel Moniz |
E221694
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Moniz |
E720962
|
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: Moniz | Statement: [Isabel Moniz, familyName, Moniz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moniz Context triple: [Isabel Moniz, familyName, Moniz]
-
A.
Moniz
chosen
Moniz is a Portuguese surname borne by various notable figures in Portugal’s cultural and public life.
-
B.
Collip
Collip is a surname most notably associated with James Collip, a Canadian biochemist who was part of the team that developed insulin as a treatment for diabetes.
-
C.
Mahuva
Mahuva is a coastal town in Gujarat, India, known for its onion production, coconut plantations, and scenic beaches along the Arabian Sea.
-
D.
Menke
Menke is a surname most notably associated with Sally Menke, the acclaimed American film editor known for her long-time collaboration with director Quentin Tarantino.
-
E.
Mandegusu
Mandegusu is an alternate name for Simbo, an island in the Western Province of the Solomon Islands in the South Pacific.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda9ecef48190b8aa0e316d07cec7 |
completed | April 1, 2026, 8:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d066521f288190a54b1199284db7a4 |
completed | April 4, 2026, 1:16 a.m. |
Created at: March 30, 2026, 7:28 p.m.