Triple
T6455547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funeral |
E141984
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Mahogany |
E581523
|
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: Mahogany | Statement: [Funeral, hasPart, Mahogany]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahogany Context triple: [Funeral, hasPart, Mahogany]
-
A.
Mahogany
Mahogany is a music producer known for contributing to Mariah Carey's work, including on her album "The Emancipation of Mimi."
-
B.
De Wood
De Wood is a specific variant or form of wood distinguished from the general category of wood materials.
-
C.
Touchwood
Touchwood is a large modern shopping and leisure centre in Solihull, England, featuring a wide range of retail stores, restaurants, and entertainment facilities.
-
D.
Sakao
Sakao is an Oceanic language spoken on the island of Espiritu Santo in Vanuatu, noted for its complex phonology and distinctive sound changes.
-
E.
Swietenia mahagoni
chosen
Swietenia mahagoni is a tropical hardwood tree species, commonly known as West Indian mahogany, valued for its high-quality timber and ornamental use.
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d4d588819090e8a56c46c0bfe9 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bdc4e808190a7c24b963ab0aa30 |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:48 p.m.