Triple
T7802376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beauty and the Beast (musical) |
E180460
|
entity |
| Predicate | featuresSong |
P2152
|
FINISHED |
| Object | Gaston |
E231330
|
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: Gaston | Statement: [Beauty and the Beast (musical), featuresSong, Gaston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gaston Context triple: [Beauty and the Beast (musical), featuresSong, Gaston]
-
A.
Gaston
chosen
Gaston is a masculine given name of French origin commonly used in Francophone countries and beyond.
-
B.
Gaspard
Gaspard is a French masculine given name historically borne by notable figures such as nobles, military leaders, and artists.
-
C.
Gervais
Gervais is the surname of British comedian, actor, writer, and director Ricky Gervais, best known for co-creating and starring in the original UK version of "The Office."
-
D.
Greuze
Greuze is a French surname most famously associated with Jean-Baptiste Greuze, an 18th-century painter known for his sentimental and moralizing genre scenes.
-
E.
Luc Oursel
Luc Oursel was a French business executive best known for leading the nuclear energy company Areva during the early 2010s.
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae988bc2081909870bae1c2e9c238 |
completed | March 30, 2026, 9:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5a2fd718819097cee2482bca74ad |
completed | March 31, 2026, 5:22 a.m. |
Created at: March 30, 2026, 4:33 p.m.