Triple
T11950088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sordello |
E284402
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Palma |
E465110
|
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: Palma | Statement: [Sordello, hasCharacter, Palma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palma Context triple: [Sordello, hasCharacter, Palma]
-
A.
Palma
chosen
Palma is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
-
B.
Palma de Mallorca
Palma de Mallorca is the historic coastal city and major tourist destination that serves as the political, cultural, and economic center of Spain’s Balearic Islands.
-
C.
Mahón
Mahón is the principal city and administrative center of the Spanish Balearic island of Menorca, known for its large natural harbor and historic architecture.
-
D.
Denia
Denia is a coastal city on Spain’s Costa Blanca known for its historic castle, Mediterranean beaches, and vibrant port.
-
E.
Marbella
Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
- 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_69d6ab2db38c8190b1f0ed6663ef8ada |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90364c2608190a3946c9595c71164 |
completed | April 10, 2026, 2:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f458f16f088190a0005ff0fd4f547f |
completed | May 1, 2026, 7:40 a.m. |
Created at: April 8, 2026, 9:45 p.m.