Triple
T1009802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ezra Pound |
E21795
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Paris, France |
E568
|
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: Paris, France | Statement: [Ezra Pound, residence, Paris, France]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paris, France Context triple: [Ezra Pound, residence, Paris, France]
-
A.
Paris
chosen
Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
-
B.
Paris
Paris is a prince of Troy in Greek mythology, best known for judging the beauty contest of the goddesses and for abducting Helen, which sparked the Trojan War.
-
C.
Fontainebleau, France
Fontainebleau, France is a historic town southeast of Paris best known for its vast forest and royal château, long associated with French monarchs and outdoor recreation.
-
D.
Neuilly-sur-Seine, France
Neuilly-sur-Seine, France is an affluent suburban commune just west of central Paris, known for its high standard of living and status as one of the wealthiest areas in the country.
-
E.
Palaiseau
Palaiseau is a suburban commune in the southern outskirts of Paris, France, known for hosting major scientific and engineering institutions.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a3cb608190a2de34a09cd55146 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac89f9d7688190836459b2453e5e2b |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:41 p.m.