Triple
T3309667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth of France |
E69538
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Madrid |
E4617
|
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: Madrid | Statement: [Elisabeth of France, deathPlace, Madrid]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Madrid Context triple: [Elisabeth of France, deathPlace, Madrid]
-
A.
Madrid
chosen
Madrid is the capital and largest city of Spain, renowned for its rich cultural heritage, historic architecture, and vibrant arts and nightlife scenes.
-
B.
Madrid
Madrid is a municipality in the Cundinamarca department of Colombia, located near Bogotá and known for its floriculture and agricultural production.
-
C.
Barcelona
Barcelona is a major Spanish Mediterranean city renowned for its distinctive Catalan culture, Gaudí architecture, and vibrant arts and nightlife scenes.
-
D.
Bilbao
Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
-
E.
Valencia
Valencia is a municipality in the Philippine province of Negros Oriental known for its cool climate, geothermal energy resources, and natural attractions such as waterfalls and mountain landscapes.
- 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_69ad859f218081909458d2cebbf57565 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0eb6dd08190bab1ce80f417966a |
completed | March 8, 2026, 5:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b34bb1c468819083b50b5858f8afe0 |
completed | March 12, 2026, 11:26 p.m. |
Created at: March 8, 2026, 3:11 p.m.