Triple
T276004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pablo Picasso |
E5251
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Pablo |
E30439
|
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: Pablo | Statement: [Pablo Picasso, givenName, Pablo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pablo Context triple: [Pablo Picasso, givenName, Pablo]
-
A.
Pablo
chosen
Pablo is a given name, especially common in Spanish-speaking countries, that corresponds to the English name Paul.
-
B.
Eduardo
Eduardo is a masculine given name commonly used in Spanish and Portuguese-speaking countries, equivalent to the English name Edward.
-
C.
Pedro
Pedro is the Spanish and Portuguese given name equivalent to the English name Peter and the French name Pierre.
-
D.
José
José is the given first name of Major League Baseball manager and former player Alex Cora.
-
E.
Paolo
Paolo is the Italian form of the given name Paul, commonly used in Italy and other Italian-speaking communities.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3ab9c2ac4819089557c7f0335c520 |
completed | March 1, 2026, 2:59 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.