Triple
T2219000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York–Paris |
E48096
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | French Bee |
E10909
|
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: French Bee | Statement: [New York–Paris, servedBy, French Bee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: French Bee Context triple: [New York–Paris, servedBy, French Bee]
-
A.
French Bee
chosen
French Bee is a French low-cost, long-haul airline specializing in transatlantic and Indian Ocean routes.
-
B.
Barberini bees
The Barberini bees are a heraldic emblem of the powerful Italian Barberini family, prominently associated with Pope Urban VIII and widely used in Baroque art and architecture in Rome.
-
C.
The Bee
The Bee is the 16th chapter of the Qur'an, known for its emphasis on God's blessings, signs in nature, and guidance for righteous living.
-
D.
Angoumois
Angoumois is a historic province in western France centered around the town of Angoulême, known for its role in the old French provincial system.
-
E.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc011d50c8190b1c375cc633f8189 |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae655b369c8190a5d12b87401534d7 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:46 p.m.