Triple
T8688677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Javel district |
E206229
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Eau de Javel |
E297566
|
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: Eau de Javel | Statement: [Javel district, namedAfter, Eau de Javel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eau de Javel Context triple: [Javel district, namedAfter, Eau de Javel]
-
A.
Lemonal
Lemonal is a small rural village in Belize known for its traditional Creole community and proximity to wetlands and wildlife.
-
B.
Domestos
chosen
Domestos is a widely sold household cleaning and disinfectant brand known for its powerful bleach-based products.
-
C.
Eau de Cologne
Eau de Cologne is a light, citrus-based perfume originating in 18th-century Cologne, Germany, that became one of the earliest and most influential modern fragrances.
-
D.
Skoal
Skoal is a leading U.S. smokeless tobacco brand best known for its moist snuff products.
-
E.
Brillo
Brillo is a lightweight, Android-based operating system developed by Google for powering and managing Internet of Things (IoT) devices.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc57334b0c8190903a5a1784e74791 |
completed | March 31, 2026, 11:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cef3d6904c8190a8456a99dae87bf2 |
completed | April 2, 2026, 10:55 p.m. |
Created at: March 30, 2026, 6:33 p.m.