Triple
T4166955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zakros |
E84468
|
entity |
| Predicate | comparableTo |
P278
|
FINISHED |
| Object | Malia |
E86664
|
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: Malia | Statement: [Zakros, comparableTo, Malia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malia Context triple: [Zakros, comparableTo, Malia]
-
A.
Malia
Malia is the elder daughter of former U.S. President Barack Obama and former First Lady Michelle Obama.
-
B.
Malia
chosen
Malia is an important Minoan Bronze Age palace complex and archaeological site on the northern coast of Crete.
-
C.
Melanija
Melanija is the Slovene given name of Melania Trump, the former First Lady of the United States and wife of Donald Trump.
-
D.
Xania
Xania is a glamorous pop star and key supporting character in the 2006 comedy film "The Pink Panther."
-
E.
Mella
Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c43a7481909eed7cb8c14deb0c |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f4a022c819092b5489aa47f430c |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:44 p.m.